Marie-Amandine Pinault-Thaury
email: marie-amandine.pinault-thaury@uvsq.fr

Ingrid Stenger

Rémi Gillet

Solange Temgoua

Ekaterina Chikoidze

Yves Dumont

François Jomard

Thierry Kociniewski

Julien Barjon

Attractive electron mobility in (113) n-type phosphorus-doped homoepitaxial diamond

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Attractive electron mobility in (113) n-type phosphorus-doped homoepitaxial diamond

Introduction

With tremendous physical properties, diamond is considered to be the ultimate semiconductor for high power electronics [START_REF] Shikata | Single crystal diamond wafers for high power electronics[END_REF]. Indeed, diamond is awaited to endure high electric fields with low leakage current. It is then a candidate of choice for high voltage and high temperature power electronics. Compared to other wide bandgap semiconductors (ex: ZnO and GaN), high mobility of the holes is a prime advantage for bipolar devices. However, diamond presents a doping asymmetry (as ZnO for example). While its p-type doping with boron in substitution for carbon is easy [START_REF] Bogdanov | Synthesis of thick and high-quality homoepitaxial diamond with high boron doping level: oxygen effect[END_REF] [3] [START_REF] Achard | Freestanding CVD boron doped diamond single crystals: A substrate for vertical power electronic devices?[END_REF], its n-type conductivity is difficult to achieve. Being a major issue for the fabrication of diamond-based bipolar devices, n-type doping is an active research topic [START_REF] Roschewsky | Spinorbit torques in ferrimagnetic GdFeCo alloys[END_REF] [6] [START_REF] Nadolinny | EPR of synthetic diamond heavily doped with phosphorus[END_REF].

Even if some incursions were made on the (110) orientation [START_REF] Balasubramaniam | Thick homoepitaxial (110)-oriented phosphorus-doped n-type diamond[END_REF], the conventional crystalline orientations used for diamond are (111), that especially suffers from easy crystalline defect formation, and (100), on which better electronic properties are generally observed on larger surfaces [START_REF] Pinault-Thaury | High fraction of substitutional phosphorus in a (100) diamond epilayer with low surface roughness[END_REF]. Lying in between (111) and (100) [START_REF] Lesik | Preferential orientation of NV defects in CVD diamond films grown on (113)-oriented substrates[END_REF], (113) is a stable growth orientation during chemical vapor deposition (CVD) [START_REF] Snail | Confirmation of {113} facets on diamond grown by chemical vapor deposition[END_REF] and could allow obtaining enlarged crystals [START_REF] Silva | Single crystal CVD diamond growth strategy by the use of a 3D geometrical model: growth on (113) oriented substrates[END_REF]. The high potential of the (113) orientation was revealed recently thanks to the works of Lesik et al. [START_REF] Lesik | Preferential orientation of NV defects in CVD diamond films grown on (113)-oriented substrates[END_REF] and Tallaire et al. [START_REF] Tallaire | Growth of thick and heavily boron-doped (113)-oriented CVD diamond films[END_REF]. For achieving a given film thickness together with a dedicated doping level, a wide growth window is a precious advantage. Tallaire et al. [START_REF] Tallaire | Growth of thick and heavily boron-doped (113)-oriented CVD diamond films[END_REF] show that the use of (113) orientation substrates for p-type boron doped diamond homoepitaxy allows extension of the optimal MPCVD growth window, compared to conventional (100) orientation (ex: higher growth temperatures and growth rates). Moreover, the (113) p-type doping has been reached with homoepilayers presenting high crystalline quality whatever the layer thicknesses, varying from a few hundred of micrometers to free-standing plates. No unepitaxial defects (as crystallites) were observed unlike on (100) orientation. A freestanding plate of (113) heavily boron doped CVD diamond exhibits low resistivity compared to (100) orientation. Even if heavily boron doped diamond is reached on (111) orientation substrates, the formation of twins and growth defects forbidden the growth of thick high boron doped (111) layers. Thus, compare to (100) and (111) orientations, it is possible to consider highly conductive (113) substrates that are required, for example, in vertical Schottky diodes. By improving boron doping efficiency in high-quality thick diamond, (113) orientation could represent a good tradeoff between (100) and (111) orientations. As a result, the use of (113) diamond seems very attractive for power electronic devices as bipolar devices.

With an ionization energy of 0.6 eV [START_REF] Koizumi | Growth and characterization of phosphorous doped {111} homoepitaxial diamond thin films[END_REF] phosphorus is the donor that gives the highest n-type conductivities in diamond [START_REF] Koizumi | Phosphorus-doped chemical vapor deposition of diamond[END_REF] [16] [START_REF] Pinault-Thaury | Phosphorus donor incorporation in (1 0 0) homoepitaxial diamond: Role of the lateral growth[END_REF] [START_REF] Kato | Okushi "n-type doping of (001)-oriented single-crystalline diamond by phosphorus[END_REF]. While phosphorus atoms get incorporated in substitutional sites in (111) homoepilayers rather easily [START_REF] Hasegawa | Lattice location of phosphorus in n-type homoepitaxial diamond films grown by chemical-vapor deposition[END_REF], the growth of (100) n-type diamond with phosphorus is quite difficult and requires a specific and narrow window of growth parameters [START_REF] Pinault-Thaury | High fraction of substitutional phosphorus in a (100) diamond epilayer with low surface roughness[END_REF] [START_REF] Kato | n-type diamond growth by phosphorus doping on (0 0 1)-oriented surface[END_REF]. In our previous work [START_REF] Pinault-Thaury | Phosphorus-doped (113) CVD diamond: A breakthrough towards bipolar diamond devices[END_REF], we found a window of growth parameters that results in high crystalline quality (113) epilayers with full incorporation of phosphorus donors in carbon sites [START_REF] Pinault-Thaury | Phosphorus-doped (113) CVD diamond: A breakthrough towards bipolar diamond devices[END_REF]. The (113) phosphorus incorporation efficiency and the maximum phosphorus content lies between the reported values for (100) and (111) [START_REF] Kato | n-type diamond growth by phosphorus doping on (0 0 1)-oriented surface[END_REF] [22] [START_REF] Maida | Substrate temperature optimization for heavilyphosphorus-doped diamond films grown on vicinal (001) surfaces using high-powerdensity microwave-plasma chemical-vapor-deposition[END_REF]. Diamond use deep energy level carriers. Thus, it has increased numbers of carriers at high temperature. Donato et al. [START_REF] Donato | Diamond power devices: state of the art, modelling, figures of merit and future perspective[END_REF] recently highlights the high operating temperature of 450K by compare diamond to 4H-SiC and GaN. Even if diamond is superior at 400 K, the gap in the performance is significantly amplified above 450 K where many physical parameters are strongly modified (carrier activation, carrier mobility, density of states, etc). Hence, compare to 4H-SiC and GaN, diamond devices might present higher current density (33% and 20%, respectively), less losses (28% and 19%, respectively) and heatsink volume. As a result, new diamond power devices might find their place in the future electronics market, especially for high temperature applications, starting from 450 K (e.g. more electric aircraft).

Here, we report on the electrical properties of phosphorus-doped diamond grown on the (113) orientation. The results are confronted to those obtained on state-of-the-art (111) and (100) films containing similar phosphorus concentration. All three homoepilayers were synthetized in our MPCVD reactor. We show that our growth conditions give rise to (113) ntype layer presenting higher conductivities than a (100) film, and open new perspectives for the n-type doping of diamond and more generally for bi-polar devices.

Experiments and results

The phosphorus-doped homoepitaxial layers have been grown on type Ib high pressure high temperature (HPHT) diamond substrates. The (111) and (100) substrates present 2x2 mm² and 3x3 mm² square surfaces with a thickness of 0.5 mm and 1.5 mm, respectively. In contrast the (113) plates have a cylindrical shape (see the optical picture in the inset of Figure 1.a) with a diameter of 2 mm and a thickness of 0.5 mm [START_REF] Lesik | Preferential orientation of NV defects in CVD diamond films grown on (113)-oriented substrates[END_REF]. The miscut angle of each substrate has been measured by X ray diffraction. It is of 2.5° and 1.5° along random directions for (111) and ( 113) plates, and of 3.5° along [110] directions for the (100) sample. Before introduction of the substrates into the growth reactor, organic and metallic contaminations were removed with a chemical treatment [START_REF] Pinault-Thaury | Phosphorus donor incorporation in (1 0 0) homoepitaxial diamond: Role of the lateral growth[END_REF].

Samples were fabricated in our laboratory-built reactor allowing microwave plasma chemical vapor deposition (MPCVD) associated with the metal-organic technology for doping using a liquid phosphorus precursor [START_REF] Kociniewski | ntype CVD diamond doped with phosphorus using the MOCVD technology for dopant incorporation[END_REF]. As a dopant precursor we used tertiarybutylphosphine (TBP: C4H11P) vapor diluted in hydrogen. The substrate temperature was measured with a dualwavelength Williamson pyrometer (the relative uncertainty is 10%). Growth parameters specific to each surface orientation have been used to achieve high crystalline quality and an almost complete incorporation of phosphorus in donor sites as shown in our previous works [START_REF] Pinault-Thaury | High fraction of substitutional phosphorus in a (100) diamond epilayer with low surface roughness[END_REF] [16] [21] [START_REF] Barjon | Determination of the phosphorus content in diamond using cathodoluminescence spectroscopy[END_REF]. Considering the notations [P] for the phosphorus atomic content and ND for the phosphorus donor concentration, our layers present [P]  ND. For the (111) [START_REF] Maida | Substrate temperature optimization for heavilyphosphorus-doped diamond films grown on vicinal (001) surfaces using high-powerdensity microwave-plasma chemical-vapor-deposition[END_REF] and (100) [START_REF] Pinault-Thaury | High fraction of substitutional phosphorus in a (100) diamond epilayer with low surface roughness[END_REF] surfaces, the n-type doping was carried out with TBP giving phosphorus concentration in the gas phase at a level of [P]/[C]gas = 0.01% and 1.2%, respectively. In contrast, the n-type doping of the (113) layers was non-intentionally doping (doping due to residual phosphorus in the vacuum chamber), as shown in our previous report [START_REF] Pinault-Thaury | Phosphorus-doped (113) CVD diamond: A breakthrough towards bipolar diamond devices[END_REF]. The samples are labeled A, B, C with respect to the (100), ( 113) and (111) orientations. The growth parameters and the main characteristics of the samples are summarized in Table 1.

Secondary ion mass spectrometry (SIMS) was used to measure the phosphorus content in the samples (the relative uncertainty is ~10%) as described elsewhere [START_REF] Pinault-Thaury | Phosphorus donor incorporation in (1 0 0) homoepitaxial diamond: Role of the lateral growth[END_REF] [START_REF] Pinault-Thaury | Phosphorus-doped (113) CVD diamond: A breakthrough towards bipolar diamond devices[END_REF]. The phosphorus content in the three epilayers is homogenous in-depth, as attested by the almost flat SIMS profiles from the surface to the epilayer interface with the HPHT substrate. As an example Figure 1.a shows the phosphorus concentration profile of sample B made on (113) orientation. The three samples present comparable phosphorus concentration around 1-2x10 18 at/cm 3 . For the (113) sample, this value is in between our previous reported values, 7x10 16 and 3x10 19 at/cm 3 , for non-intentionally doped (113) homoepilayers grown with similar MPCVD conditions [START_REF] Tallaire | Growth of thick and heavily boron-doped (113)-oriented CVD diamond films[END_REF]. The phosphorus atoms incorporated in the non-intentionally doped layers are not coming from the gas line but from the reactor itself. More precisely some internal parts of the vacuum chamber are suspected to outgassing phosphorus from their surface thanks to the heat of plasma radiations. The released phosphorus atoms are then coming into the gas mixture and participate to the growth. The internal parts of the vacuum chamber are polluted with phosphorus because of the use of various and high TBP overpressure needed for other type of growth studies [START_REF] Temahuki | New Process for Electrical Contacts on (100) N-type Diamond[END_REF]. Even if it is time consuming and expensive, the control and decrease of the phosphorus concentration in (113) orientation is possible thanks to clean-up and/or replacement of critical internal parts of the vacuum chamber. Once done, at first the use of TBP low overpressure should be favored to reach low phosphorus concentrations in (113) orientation. 113) and ( 111) diamond substrates and physical properties extracted from the SIMS and electrical measurements analysis.

Sample

The optical quality has been estimated using cathodoluminescence (CL) spectroscopy on an equipment optimized to analyze the 200-1000 nm range emission [START_REF] Barjon | Optical spectroscopy of doped diamond layers[END_REF]. The samples are cooled down in a JEOL7001F scanning electron microscope (SEM) close to the liquid helium temperature. The CL spectra were obtained using a 10 keV electron beam which corresponds to approximately 0.9 µm of penetration depth of electrons. For all the samples, the CL spectra exhibit a dominant peak corresponding to the neutral phosphorus bound exciton recombination P 0 XTO at 5.19 eV when assisted by the emission of a transverse optical (TO) phonon [START_REF] Barjon | Luminescence Spectroscopy of Bound Excitons in Diamond[END_REF]. Figure 1.b shows the CL spectrum of sample B made on (113) orientation. The no-phonon phosphorusbound exciton recombination P 0 XNP is also observed at 5.33 eV. The linewidths of the P 0 XTO and P 0 XNP line are around 10.5 meV and 2.2 meV indicating that the crystallinity of the epilayers is similar to good quality (111) phosphorus doped epilayers [START_REF] Teofilov | Bound exciton luminescence related to phosphorus donors in CVD diamond[END_REF]. The presence of uncompensated phosphorus donors in our phosphorus-doped samples has been attested by infrared (IR) absorption in a transmission geometry. The experiment was performed at 90 K in a BOMEM DA8 Fourier-transform interferometer (FTIR), from 1800 to 8500 cm -1 using an InSb detector and a spectral resolution of 2 cm -1 . For the three samples, we observe the absorption line at 4540 cm -1 corresponding to the 1s → 2p+/-electronic transition of neutral phosphorus [START_REF] Stenger | Quantitative analysis of electronic absorption of phosphorus donors in diamond[END_REF]. Figure 1.c shows the FTIR spectrum of sample B made on (113) orientation. Since the absorption coefficient is proportional [START_REF] Stenger | Quantitative analysis of electronic absorption of phosphorus donors in diamond[END_REF] to the neutral phosphorus donor concentration ND 0 =ND-NA, (where NA is the concentration of compensating acceptors) the absorption experiments evidence that the studied epilayers present a significant amount of uncompensated phosphorus donors. As a result, a n-type electrical conductivity is expected for phosphorus-doped diamond grown on the three surface orientations.

The DC electrical measurements were performed by resistivity and Hall effect in a Van der Pauw configuration from ~ 300K to 850K under a DC magnetic field of 1.6 T, on a high impedance laboratory developed setup. Prior to the electrical measurements, the as-grown diamond film surfaces were chemically oxidized in order to remove the surface conductive layer due to the hydrogen termination [START_REF] Kociniewski | ntype CVD diamond doped with phosphorus using the MOCVD technology for dopant incorporation[END_REF]. For electrical contacts on the (100) epilayer (sample A), our surface microstructuration process [START_REF] Temahuki | New Process for Electrical Contacts on (100) N-type Diamond[END_REF] was applied before deposition of metallic contacts (Ti/Au) by sputtering. For epilayers grown on ( 113) and ( 111) orientations (samples B and C), the electrical contacts were made with Ti/Pt/Au electrods. All contacts have been annealed at 600°C for 30 min under N2 atmosphere and present a sufficiently low rectifying characteristic to ensure reliable data from electrical measurements. A negative Hall voltage was measured over the whole 300-850K temperature range, showing the conductivity is driven by electrons (n-type) in our samples.

Figure 2.a shows the temperature dependence of the resistivity, ρ (lozenges), and the carrier concentration, n (circles), for the 3 samples, A, B and C, grown on (100), ( 113) and (111) orientations, respectively. Free electrons are thermally activated, as a result of phosphorus donor ionization. From resistivity versus 1000/T dependence, it is clear that band conduction is the dominant conduction process observed for the three surface orientations over the temperature range. It leads to an almost exponential decrease of the layer resistivity with temperature (and the related increase of the carrier concentration: see fitted curves in Fig. 2(a)). In the low temperature region, a weak deviation is observed, due to variable range hopping [START_REF] Mott | Electronic Processes in Noncrystalline Materials[END_REF]. The (100) sample presents the highest resistivity. At room temperature (RT), the (113) and (111) epilayers present a similar resistivity in the 10 5 Ω.cm range which is more than 10 times lower than the one of the (100) layer.

From the temperature dependence of the carrier concentration, we deduce independently the impurity-to-band activation energy EA and the compensation ratio k = NA/ND. See ref [START_REF] Stenger | Impurity-to-band activation energy in phosphorus doped diamond[END_REF] for more details on the fitting procedure. The extracted values are reported in Table 1 and the fitted curves are plotted (lines) in Fig. 2.a. The (111) sample presents a much lower compensation ratio of 8% together with an activation energy of 0.59 eV as usually reported previously for n-type (111) [START_REF] Koizumi | n-Type doping of diamond[END_REF]. The (100) film shows a high compensation ratio of 86% with a lower activation energy of 0.56 eV, in accordance with previous reports [START_REF] Kato | n-Type Diamond Gowth by Phosphorus Doping[END_REF] [START_REF] Kato | Energy level of compensator states in (001) phosphorus-doped diamond[END_REF]. In the case of (113) epilayer, the compensation ratio and the activation energy are close to the one of the (100) sample: 80% and 0.55 eV, respectively. The SIMS analysis reveals boron contamination in the (111) film at the level of 2x10 16 at/cm 3 while no boron is detected in the (113) and (100) samples (even by CL spectroscopy: [B] < 10 14 at/cm 3 ). This suggests that the compensating acceptors are mainly coming from other defects than boron (ex: complexes involving carbon vacancies or hydrogen impurities) [START_REF] Jones | Limitations to n-type doping in diamond: The phosphorus-vacancy complex[END_REF]. The identification of compensating centers is still an open issue for improving the conductivity of n-type diamond and remains under investigation. However, one can explain their origins. Indeed, diamond epitaxy results from a competition between diamond etching and diamond growth thanks to the high level of hydrogen contained in the gas mixture (more than 90%). When the HPHT Ib substrate is exposed to the plasma, its top surface is etched only in the first stage of the layer epitaxy while its edges are longer etched before being covered by diamond layer over the growth process. Impurities coming from the substrate (as nitrogen) are then released in the gas mixture. Moreover, incorporation of other impurities into the gas mixture might also come from the internal parts of the vacuum chamber due to outgassing with plasma radiation heating (as boron). All those contaminating impurities in the gas mixture participate to the growth process. Structural defects (as dislocations) might appear also during the epitaxial growth. Without being directly and easily observable, those defects can act as compensators by themselves (boron, dislocations, etc.) or by complexing with others (N-V, P-V, P-H, V-H, etc.). Thus, the origin of compensators can come from contaminations from the substrate and the internal parts of the reactors but also from structural defects induced by the growth itself. While diamond-based devices are supposed to work at high temperature (>150°C), it is worth to evaluate the temperature dependence of the electron mobility, µn, (reported in Figure 2.b) for each diamond sample. For the (111) orientation, µn presents a maximum value of 308 cm²/V.s at RT and then decreases with increasing temperature. (100) and (113) samples present increasing µn up to ~450K, with maximum values, respectively of 117 and 355 cm²/V.s., followed by a more or less significant decrease. Whatever the temperature, µn of (113) sample always remains higher than 100 cm²/Vs. unlike (111) and (100) samples. From Log(µn) versus Log(T) dependence, one can distinguish (i) the high-T behavior mostly due to lattice scatterings (acoustic phonons, optical phonons, intervalley phonons) with T -β dependence where β ranges from 2 to 0 and a value of 3/2 for pure acoustic phonons scattering [START_REF] Pernot | Electron mobility in phosphorus doped {111} homoepitaxial diamond[END_REF], and (ii) the lower-T behavior T α associated all sources of defects (ionized or neutral impurities). Indeed, according to Pernot et al. [START_REF] Pernot | Electron mobility in phosphorus doped {111} homoepitaxial diamond[END_REF] on such temperature range, the factor limiting the electron mobility in (111) diamond epilayers is mainly intrinsic scattering due to acoustic phonons, thanks to the relatively weak compensation of the (111) layers. In our case, we found values of high-T (T > 450 K) lattice contribution β coefficient of 0.9, 1.8 and 2 for (100), ( 111) and (113) respective orientations. From low-T behavior (300K-450K), electron mobility of (100) and (113) samples is mostly limited by the ionized impurities, probably associated residual acceptors involved in high compensation levels. Despite the fact that (113) film is highly compensated, it is remarkable that its electron mobility stays at higher values than the one reached on (100) layer over the whole temperature range and on (111) layer above 450K. Furthermore, if we extrapolate the high-T dependence of Log(µn) versus Log(T) to lower temperatures, associated mostly to lattice scatterings (see dashed lines in figure 2.b), we can expect even higher electron mobility on the (113) orientation, for less defective diamond (less ionized and/or neutral impurities). Then, improving the growth conditions or finding ex-situ treatment to reduce compensation in (113) phosphorus-doped diamond might allow higher electron mobilities, even higher than 1000 cm²/V.s., the one predicted for (111) [START_REF] Pernot | Hall electron mobility in diamond[END_REF].

Conclusion

In this work we show that the growth window found for (113) phosphorus-doped diamond allows the synthesis of n-type conductive layer. Even with high compensation ratio the (113) CVD layer presents better electrical properties than on (100) orientation, currently preferred for electronics. Such results show that there is room for improvement on the (113) orientation. Indeed understanding the limitations of electron mobility in n-type diamond will be of prime importance to develop diamond electronics. Our results are quite attractive for the realization of future (113) diamond bipolar devices.

Figure 1 :

 1 Figure 1: Physical characteristics of phosphorus-doped epilayer grown on a (113) substrate (sample B): (a) SIMS profile of the phosphorus concentration) (inset: optical image of the sample surface); (b) CL spectrum attesting of the incorporation of phosphorus in donor sites through the bound exciton P°XTO; (c) FTIR absorption spectrum showing the presence of uncompensated phosphorus donors, through the observation of the 1s→2p+/-electronic transition from neutral phosphorus donors.

Figure 2 :

 2 Figure 2: Electrical properties of the homoepitaxial diamond layers grown on (100), (113) and (111) surfaces having the same phosphorus concentration [P] = 1-2x10 18 at/cm 3 : temperature dependences of (a) electron concentration, n (circles, left axis), and layer resistivity, ρ (lozenges, right axis); (b) electron mobility, µn (in log-log scale). For Log(µn) versus Log(T), the dashed lines of the (100) and (113) samples are extrapolations of the lattice scatterings high-T behavior.

Table 1 :

 1 Parameters for the growth of homoepitaxial layers on (100), (

	A	B	C

Acknowledgements

The authors would like to thank C. MER-CALFATI and B. BERINI for technical support on metal deposition; J. LABBÉ, Y. OUALI, N. TEMAHUKI for realization of the Hall effect measurements; and the French National Research Agency (ANR) for funding this work under the project MOVeToDiam N° ANR-17-CE05-0019-02 and the CNRS under the Tremplin 2019 grant.


Hee-Soo Choi
email: hee-soo.choi@loria.fr

Bruno Guillaume
email: bruno.guillaume@loria.fr

Guy Perrier
email: guy.perrier@loria.fr

Investigating Dominant Word Order on Universal Dependencies with Graph Rewriting

This paper details experiments we performed on the Universal Dependencies 2.7 corpora in order to investigate the dominant word order in the available languages. For this purpose, we used a graph rewriting tool, GREW, which allowed us to go beyond the surface annotations and identify the implicit subjects. We first measured the distribution of the six different word orders (SVO, SOV, VSO, VOS, OVS, OSV) in the corpora and investigated when there was a significant difference in the corpora within a given language. Then, we compared the obtained results with information provided in the WALS database (Dryer and Haspelmath, 2013) and in Östling (2015). Finally, we examined the impact of using a graph rewriting tool for this task. The tools and resources used for this research are all freely available.

Introduction

Language typology has proven to be useful in natural language processing (NLP) [START_REF] Bender | Linguistic typology in natural language processing[END_REF][START_REF] Helen | Survey on the use of typological information in natural language processing[END_REF], for example for improving performance in language transfer [START_REF] Naseem | Selective sharing for multilingual dependency parsing[END_REF][START_REF] Ahmad | On difficulties of cross-lingual transfer with order differences: A case study on dependency parsing[END_REF] and joint learning.

As noted by O'Horan et al. ( 2016) "WALS is currently by far the most commonly-used typological resource in NLP due to its broad coverage of features and languages". However, the WALS database (Dryer and Haspelmath, 2013) has been compiled from the work of 55 linguists1 and is not systemically based on a large quantity of data. Moreover, it does not provide all the considered features for all the languages it covers.

On the other hand, the Universal Dependencies (UD) framework [START_REF] Nivre | Universal dependencies v1: A multilingual treebank collection[END_REF] provides a large number of corpora annotated in dependency syntax (in version 2.7, there are 183 corpora for 104 languages).

We decided to automatically extract from the UD corpora one of the most used features in NLP, the dominant word order, i.e. the way the subject (S), verb (V) and object (O) are ordered in a language (feature 81A in WALS). To do so, we use a freely available graph rewriting tool, which allows us to perform complex searches, to take into account the context of the construction and to add or modify the existing annotations to expose relations which are not directly accessible in the corpora.

These experiments led us to define what is a dominant word order, to observe the distribution in word orders within the corpora of a given language, to determine the frequency of the different word orders in all the considered corpora, and to compare the obtained results with those of existing databases, including WALS.

Previous Work

UD-based Typology

Dependency treebanks have already been used to investigate the order of subject and object in different languages. [START_REF] Liu | Dependency direction as a means of word-order typology: A method based on dependency treebanks[END_REF] presented a statistical overview of several binary parameters including SV vs VS, OV vs VO on 20 languages and compared their results with WALS'. However, their experiments were conducted before the UD framework, on treebanks with different annotation schemes.

To our knowledge, the closest work to ours is that of Östling (2015). He considered word order typology based upon the translated and aligned new testament in almost 1,000 languages and compared his results with WALS data. The main difference with our work is that for us, identifying the dominant word order is our goal and not just a production allowing the evaluation of a system. Besides, the data used in his experiment was generated automatically, rather than (at least partially) manually annotated. The produced data is available, so we were able to compare our results with his.

UD treebanks were also used to study word order freedom. [START_REF] Futrell | Quantifying word order freedom in dependency corpora[END_REF] and [START_REF] Berdicevskis | Corpus evidence for word order freezing in russian and german[END_REF] examined the word order freedom of subjects and objects, focusing on the correlation with case marking.

More recently, [START_REF] Alzetta | Universal dependencies and quantitative typological trends. a case study on word order[END_REF] applied a plausibility assessment algorithm to the UD treebanks to assess its usability in identifying typological features. They focused on the subject-verb and adjective-noun orders and experimented with three languages, English, Italian and Spanish. While their analysis is quite thorough, the algorithm they employed is not available, so their work cannot be extended.

Finally, Gerdes et al. (2019b) tested some of Greenberg's universals2 on UD. Their work does include word order information but focuses on only two classes (the verb is before or after the object/subject). Besides, they decided to merge the treebanks for multi-corpora languages.

Enriching UD Annotations

There is no easy way to decide which dependency relations should be taken into account in order to observe word order dominance. In basic UD annotations, the tree restriction of usual dependency annotation frameworks impose some arbitrary choices: it is not possible to consider that the same token can be used twice as subject of different verbs. In our study, we try to overcome this limitation by making explicit some "syntactic" relations which cannot be expressed in UD (see Section 4.3). In Section 7, we compare what we observe using what we call implicit subjects with the same analysis on basic UD annotations only.

Similar types of enrichment have been proposed before, namely the Enhanced Universal Dependencies and the Deep Universal Dependencies.

Enhanced Universal Dependencies (EUD) were proposed in [START_REF] Schuster | Enhanced English Universal Dependencies: An improved representation for natural language understanding tasks[END_REF]. The goal of this work is to create an annotation which is more suitable for natural language understanding tasks, by making some of the implicit relations between words more explicit. Five kinds of new annotations are considered in this framework3 : adding null nodes for elided predicates, propagating relations over conjuncts, adding subject relations for control and raising constructions, adding coreference in relative clause constructions and modifier labels that contain the preposition or other casemarking information. Unfortunately, adding these annotations requires manual annotation, therefore the EUD annotation layer is available in only 34 of the 183 treebanks in version 2.7. Moreover some of these 34 treebanks have only a subpart of the five extensions mentioned above.

The goal of the Deep Universal Dependencies (DUD) [START_REF] Droganova | Towards deep Universal Dependencies[END_REF] is also to provide annotations adapted to natural language understanding. DUD expresses relations that are closer to predicate-argument structure than the annotations of EUD, using relations names (arg1, arg2, . . . ) borrowed from semantic frameworks like the Abstract Meaning Representation (AMR) [START_REF] Banarescu | Abstract meaning representation for sembanking[END_REF]. DUD is built automatically from EUD when annotations are available or with an automatic production of EUD for other corpora.4 3 Methodology

Taking the Corpora as Basis

Our study is based on the version 2.7 of UD, with 183 corpora and 104 languages available. Since our experiments consist in the extraction of statistics from data in corpora, we chose to eliminate corpora with fewer than 1,000 sentences, since we consider them too small to be representative of the language. Once this filter was applied, we obtained 141 corpora in 74 languages, which constitute the UD 2.7 1K corpus.

We decided to compile statistics at the corpus level rather than the language level, in order to observe variations between corpora of a given language and to compare the significance between them. 29 languages are represented by more than one corpus and for the 45 remaining ones we consider that "corpus equals language".

Defining a Dominant Word Order

Describing an order as a language's dominant order can have two meanings: either the order is the only possible one for the language, or the language exhibits several different orders and one is more frequently used.

In our experiments, we count the occurrences of the six possible orders in UD 2.7 1K , which means that our results are based only on the occurrence frequencies of the orders and therefore depend heavily on the composition of the corpora. Although we are aware of possible biases due to the corpus's degree of representativeness, our purpose is to determine a dominant order per corpus from raw data and to check whether we obtain results which are consistent with those of descriptive grammars.

Inspired by [START_REF] Dryer | Determining dominant word order[END_REF], we consider the most frequent order as the dominant order for a given corpus provided that it is at least twice as frequent as the next most frequent. This means that for each corpus, we observe the ratio between the number of occurrences of the most frequent order with respect to the number of occurrences of the second most frequent order; if the ratio is greater than or equal to 2, the most frequent order is the dominant order, else we consider the corpus to be NDO (No Dominant Order). This allows us to classify as NDO corpora exhibiting little differences between two orders (for example, GERMAN-GSD with implicit subjects shows 35.7% SOV and 34.8% SVO). When the results differ among corpora of a given language, we study the corpora on a case by case basis.

Dealing with UD Specifics

In UD [START_REF] Nivre | Universal dependencies v1: A multilingual treebank collection[END_REF], a given label can be ambiguous with respect to syntactic relations. For example, the labels xcomp and ccomp are used for both direct and indirect objects. Because of this limitation, we restrict our study to nominal objects, i.e. to obj relations. A similar difficulty arises with subjects. In UD, a personal subject is annotated with a relation subj, while an impersonal subject is annotated with the relation expl, which is also used for other relations with expletives. This ambiguity leads us to ignore impersonal subjects in our study5 .

Due to the tree constraint, some relations are not explicitly given in the data. In our study, this can affect subjects that can be shared by several verbs in coordination or through control of raising verbs. We call these hidden relations implicit relations.

For instance, consider the Polish sentence: There is an implicit subject relation between ma and Kuba which is not represented in the UD annotation. In our experiments, we ran an extended search on UD data with implicit subjects that can be predicted from surface syntax. Implicit objects also exist but it is not possible to recover them automatically from surface syntax. In the previous example, tego is the object of potrzebuje but it is not possible to determine if tego is an implicit object of ma.

Besides these issues, UD 2.7 includes two codeswitching corpora: Turkish-German and Hindi-English. They were added as new "languages" and we therefore consider them here as such.

4 Going Deeper with Graph Rewriting 4.1 GREW GREW is a graph rewriting tool dedicated to NLP applications, which can be used to query treebanks using graph patterns written with a specified syntax. Given a set of queries and a set of corpora, a script produces a table with the number of occurrences of each query in each corpus (see Section 4.2, for examples). An online interface to the tool is available6 , which enables users to observe examples in context within corpora and to interactively design and debug the patterns before running the script.

GREW also allows users to describe a set of transformations and to apply them to each item in a corpus. In this paper, we use this feature to enrich the available annotations (see Section 4.3).

Extraction Patterns

The patterns we use to extract data in UD 2.7 1K include two syntactic relations: subject 7 and object. As explained in Section 3.3, only nominal objects can be reliably recovered from UD annotations. To be consistent, we use the same restriction for the subject relation and focus only on nominal subjects (nsubj), without considering clausal subjects (csubj). For instance, the GREW pattern for SVO is presented in Figure 1.

pattern { V [upos=VERB]; V -[1=nsubj|isubj]-> S; V -[1=obj]-> O; S << V; V << O } Figure 1: GREW pattern for SVO.
In UD, it is possible to include subtypes in relations, for instance the relation nsubj:pass can be used for a regular nominal subject in a passive construction. However, as these extensions are defined at the language level, we do not consider them here. The GREW syntax 1=subj|isubj allows to capture all relations that are either subj or isubj with or without subtypes.

Enriching UD Annotations

When used on UD annotations, the aforementioned extraction patterns present some limits as they only identify cases where the subject and the object are syntactically directly related to the same verb. However, there exist constructions admitting a subject and an object with two different governors. In our study, we consider two cases where the information can safely be recovered from surface annotations by adding implicit subjects, isubj, in an enriched UD annotation (see Section 3.3). 8The first case is coordination: when two clauses involving the same subject are linked by a coordinating conjunction with an ellipsis of the subject of the second clause, we add a new implicit subject to the head of the second clause. More technically, this is described by the rule in Figure 2: if two verbs V1 and V2 are linked by a conj relation and V2 does not have its own subject; then add the subject S1 of V1 as an isubj of V2. For instance in a sentence "He obtains these things, but loses the ability to manage them." a relation isubj will be added from loses to He.

The second case we consider is control or raising. In UD, this is annotated with the relation xcomp between the two verbs. We can use a rule that is similar to the one in Figure 2 with xcomp instead of conj. In the sentence "I should like to address one final point.", the enriched annotation will show a relation isubj from address to I.

rule conj { pattern { V1 [upos=VERB]; V2 [upos=VERB]; V1 -[1=conj]-> V2; V1 -[1=nsubj]-> S1; } without { V2 -[1=nsubj]-> S2; } commands { add_edge V2 -[isubj]-> S1;} }

Determining Dominant Word Order in Multi-Corpora Languages

We detail here the results obtained for multicorpora languages. For the mono-corpus languages, we examine our results as compared to WALS' and Östling (2015) in Section 6.

Intra-language Consistency

We obtain the number of occurrences of each of the six possible orders for each corpus in UD 2.7 1K . This data can be used to determine whether different corpora of a given language exhibit similar distributions. For this purpose, we compute the cosine between the 6-dimensional vectors for each corpus. This technique of comparing two feature vectors as a means of comparing two languages has already been used in several works on language typology [START_REF] Georgi | Comparing language similarity across genetic and typologically-based groupings[END_REF][START_REF] Berzak | Reconstructing native language typology from foreign language usage[END_REF].

We expect two corpora of the same language to display similar distributions and therefore expect a cosine value close to 1.

The lowest value we observe is for two corpora of Romanian. Table 1 illustrates the vectors describing the distribution of the six possible orders for the three Romanian treebanks and Figure 3 represents as a heatmap the cosine values between these vectors.

Figure 4 reports the minimum cosine value among all possible pairs of corpora for the 29 multicorpora languages.

Ten languages have a value below 0.95 and three have a value below 0.8 (Romanian, Hindi, Arabic). We present below a basic analysis of these results, either by seeking an explanation in the description of the corpora on the UD website or by asking language experts to examine the data. 3) German ( 4) Latin ( 4) French ( 7) Ancient_Greek ( 2) Czech ( 5) Dutch ( 2) Slovenian ( 2) Estonian ( 2) Norwegian ( 3) Russian ( 4) Polish (3) Icelandic ( 2) Galician ( 2) Turkish ( 4) Italian ( 6) Finnish (4) Faroese (2) Spanish (3) Swedish ( 3) English ( 6 explain the low cosine value: Dutch (0.928), French (0.912), Romanian (0.729) and Slovenian (0.947). One corpus in Romanian (ROMANIAN-NONSTANDARD) is dedicated to non-standard usage of that language (see Figure 3). Some corpora focus on specific types of texts: questions (FRENCH-FQB, which clearly stands out in Figure 5) and/or material from test suites and sentences from a reference grammar (DUTCH-ALPINO). French and Slovenian present corpora of spoken language (FRENCH-SPOKEN and SLOVENIAN-SSL). In Czech (0.925), one of the corpora (CZECH-FICTREE) contains only fiction and shows a higher proportion of SOV, while the four other Czech treebanks are clearly SVO.

Different text genres

Different text periods For two dead languages (Latin and Ancient Greek), corpora gather texts from very different historical periods, which could explain the differences. Latin texts range from 1 st century BC (LATIN-PERSEUS) to 13 th century Medieval Latin (LATIN-ITTB). For Ancient Greek, very different kinds of text are mixed: AN-CIENT GREEK-PROIEL contains both Herodotus (5 th century BC) and Bible texts 9 ; the other corpus (ANCIENT GREEK-PERSEUS) is a larger mix of several periods from Homer (8 th century BC) to Athenaeus (late second century). Undoubtedly, the fact that Latin and Ancient Greek are considered free word order languages amplifies the phenomenon. As for German, two corpora are NDO and two are SOV, GERMAN-HDT with a low ratio (2.01) and GERMAN-LIT. The latter is the only corpus to be composed of 18 th century texts.

Non-standard annotations In one of the two Hindi corpora (HINDI-HDTB), there is a large percentage of SVO cases (82.5%) where the object is a verb, in contradiction of the UD guidelines. If we consider only nominal subjects and objects in the patterns, the cosine value rises to 0.993.

Language specifics

In Arabic (modern standard), the basic order is VSO. However, SVO is used in cases of topicalization of the subject and in completives. The PADT corpus contains many titles of news articles featuring topicalization, which could explain the prevalence of SVO.

Dominant Word Order in Multi-Corpora Languages

For all multi-corpora languages with a minimum cosine value above 0.95, the dominant word order ratio consistently produces the same dominant order for all corpora of the language, except for Estonian which presents a SVO corpus (ESTONIAN-EDT) and a NDO corpus (ESTONIAN-EWT), corresponding to different text genres (fiction, news, nonfiction, academic vs blog, web, social). 14 multi-corpora languages are thus identified as SVO (Chinese, English, Faroese, Finnish, Galician, Icelandic, Indonesian, Italian, Norwegian, Polish, Portuguese, Russian, Spanish and Swedish) and four multi-corpora languages as SOV (Japanese, Korean, Persian and Turkish).

Out of the 10 multi-corpora languages with a minimum cosine value below 0.95, two present a clear dominant order SVO: French and Czech. As for Dutch and Ancient Greek, they both are NDO, but with inconsistent main orders: SOV/SVO and SVO/SOV. The six other languages present inconsistent dominant word orders. However, Romanian and Slovenian are both SVO in their standard or written form, even though one of their corpora is NDO (SVO/SOV). As for German, two out of four corpora are NDO (SOV/SVO) and two corpora are SOV. However, this result can be attributed to a threshold effect, since these two corpora present a SOV order at low ratios (2.01 for GERMAN-HDT, 2.53 for GERMAN-LIT).

Two corpora of Arabic are NDO (one is SVO/VSO and the other VSO/SVO) and one corpus is VSO. For the reasons explained in Section 5.1, we consider that the dominant order is most probably VSO. Hindi has one SOV and one NDO (SOV/SVO) corpora, but if we remove SVO occurrences probably due to annotation errors (i.e. O is a verb) in the latter, both corpora are clearly SOV. Latin is the language with the most heterogeneous corpora, with three NDO corpora (one SVO/SOV, two SOV/SVO) and one SOV corpus.

These differences can probably be explained by the time range among texts.

Regarding the two code-switching languages, Hindi-English is considered NDO (SVO/SOV) which is consistent since English is SVO and Hindi SOV. As for Turkish-German, the corpus presents a SOV order, Turkish and German having this order in common.

Comparison with other Sources

Amongst the 74 languages available in UD 2.7 1K , WALS does not cover the seven dead languages, nor the two code-switching "languages". In addition, WALS does not provide Feature 81A for six languages. In Östling (2015), 22 languages are not in the database and seven are in neither sources, Galician, Hindi-English, Turkish-German and four dead languages (Old French, Old Russian, Sanskrit, Akkadian).10 We compare our results with Feature 81A (Order of Subject, Object and Verb) in WALS11 . We have 59 languages in common and we consistently observe the same dominant word order for 48 of these. In Table 2, we detail the remaining 11 languages where our observations are not fully consistent with WALS classification. Taking into account the explanations in Section 5.2 about multi-corpora languages, we have five languages with one corpus where we disagree with WALS: Amharic, Belarusian, Greek, Mbya Guarani and Urdu.

Differences with WALS

Language UD 2.7 1K WALS Amharic 1 NDO SOV Arabic 1 VSO, 2 NDO VSO Belarusian 1 SVO NDO Estonian 1 SVO, 1 NDO SVO German 2 SOV, 2 NDO NDO Greek 1 SVO NDO Hindi 1 SOV, 1 NDO SOV Mbya Guarani 1 NDO SVO Romanian 2 SVO, 1 NDO SVO Slovenian 1 SVO, 1 NDO SVO Urdu 1 NDO SOV
Belarusian and Greek can be considered relatively free word order languages, hence the NDO order in WALS. In our results, Belarusian is SVO with a ratio of 10.43, however the BELARUSIAN-HSE corpus is based on texts included in the Belarusian-Russian parallel subcorpus of the Russian National Corpus. Russian being a SVO language, this may explain the high proportion of SVO. Moreover, it is more common to find the SVO order as the basic order in written Belarusian. Similarly, the basic order in Greek being SVO, this may explain the ratio of 7.31 of SVO order in our results.

As for Mbya Guarani and Urdu, the most frequent order corresponds to the order in WALS. Mbya Guarani is NDO (SVO/SOV) with a ratio of 1.25 and Urdu NDO (SOV/SVO) with a ratio of 1.52. Finally, Amharic has an OVS order as the most frequent order, contrary to WALS'.

There are six languages present in WALS which do not have the Feature 81A: Faroese, Kazakh, Maltese, Naija and Slovak. Our results could therefore be used to enrich WALS' data. The data presented in Östling (2015) is computed from the automatically aligned New Testament. The corpora are homogeneous and the data on which the dominant order is computed can sometimes be very small (for Hungarian, 127 structures vs 876 in our experiment). Moreover, Östling (2015) considers the single most prevalent order as the dominant one, without taking into account the difference with the second one.

Differences with

We have 52 languages in common and observe the same dominant order for 38 of these. Table 3 reports what we observe for the 14 other languages. Out of these languages, 9 NDO languages have the same first order as Östling (2015). The 5 remaining ones (Amharic, Ancient Greek, Basque, Latin and Welsh) present different first orders.

Influence of Implicit Subjects

As said earlier, we decided to enrich the basic UD annotations, but the choice we made is quite arbitrary. In order to evaluate how this may have impacted our observations, we conducted the same experiment without taking into account the implicit subjects.

Table 4 lists the five languages for which the two experiments predict a different word order for at least one corpus or different first rank in NDO ordering. Adding isubj changes the dominant word order in four corpora: CZECH-FICTREE, ESTONIAN-EWT, GERMAN-HDT and TURK-ISH GERMAN-SAGT. However, we note that in the four cases, one of the two ratios is close to the threshold. We observe an unexpected change for LATIN-LLCT which remains NDO, but with different top ranks (SOV/SVO with isubj and OSV/SVO without isubj). Latin is the language where we see the most important changes as can be observed by comparing the heatmaps in Figure 6.

Table 5 reports the corpora where the two experiments show a high difference (more than 5%) in term of first rank word order prediction. Only the WELSH-CCG corpus has a significant lower first rank with isubj, other corpora with a large difference present an higher first rank when isubj are taken into account. Again, the LATIN-LLCT exhibits a strange behavior with different first rank word order.

Conclusions and Perspectives

The main outcome of these experiments is the determination of the dominant word order for 74 languages, based on large amounts of annotated data. This result can be used for NLP applications.

On the linguistic side, our findings could be used to reinforce the results published in WALS and complete them in some cases. However, our results differ from WALS' for 11 languages, and for these, a more thorough analysis should be conducted by specialists of said languages. We are planning to experiment using graph rewriting to explore other universals, like Greenberg's [START_REF] Joseph | Some universals of grammar with particular reference to the order of meaningful elements[END_REF] or other missing features in WALS.

Graph rewriting can be used to enrich the UD annotations but it can also be used to reorganise more deeply the tree dependency graph. In Gerdes et al. (2019b), the observations were done on such a deeper reorganisation of the dependency tree structure, proposed in Surface Syntactic Universal Dependency (Gerdes et al., 2019a) which was already produced using GREW-based graph rewriting.

Our experiments can be replicated and extended: all the tools and resources are freely available and we also provide the patterns and scripts to be used 12

Figure 2 :

 2 Figure 2: GREW rule adding the isubj relation.

Figure 3 :

 3 Figure 3: Cosine values between the three Romanian corpora in UD 2.7 1K .

Figure 5 :

 5 Figure 5: Cosine values between the seven French corpora in UD 2.7 1K .

Figure 6 :

 6 Figure 6: Cosine values between the Latin corpora, with isubj on the left, without isubj on the right.

Table 1 :

 1 Distribution vectors for the Romanian treebanks.

	Four languages present
	corpora in different text genres, which could

Table 2 :

 2 Differences with WALS (for UD 2.7 1K , we detail by corpora).

Table 3 :

 3 Differences with Östling (2015) (for UD 2.7 1K , we detail by corpora).

Table 4 :

 4 Corpora for which the word order changes with/without isubj and associated ratio (in bold, corpora for which the order changes).

			Without isubj	With isubj
	Language	Corpora Order	Ratio Order	Ratio
		CAC	SVO	4.27	SVO	5.28
		CLTT	SVO	6.85	SVO	8.18
	Czech	FicTree	NDO (SVO/SOV)	1.97	SVO	2.20
		PDT	SVO	3.36	SVO	3.96
		PUD	SVO	6.58	SVO	6.17
	Estonian	EDT EWT	SVO SVO	3.80 2.05	SVO NDO (SVO/SOV)	3.19 1.70
		GSD	NDO (SOV/SVO)	1.03	NDO (SOV/SVO)	1.03
	German	HDT LIT	NDO (SOV/SVO) SOV	1.87 2.30	SOV SOV	2.01 2.53
		PUD	NDO (SOV/SVO)	1.47	NDO (SOV/SVO)	1.62
		ITTB	NDO (SVO/SOV)	1.22	NDO (SVO/SOV)	1.12
	Latin	LLCT PROIEL	NDO (OSV/SVO) NDO (SOV/SVO)	1.07 1.21	NDO (SOV/SVO) NDO (SOV/SVO)	1.40 1.16
		Perseus	SOV	2.42	SOV	2.17
	Turkish-German SAGT	NDO (SOV/SVO) 1.95	SOV	2.22

  .

	Corpora	first rank without isubj first rank with isubj	diff
	WELSH-CCG	VSO (80.6%)	VSO (71.1%)	-9.5%
	LATIN-LLCT	OSV (32.0%)	SOV (42.7%)	+10.7%
	AKKADIAN-RIAO	SOV (56.6%)	SOV (66.3%)	+9.7%
	ICELANDIC-ICEPAHC	SVO (57.0%)	SVO (63.4%)	+6.4%
	WOLOF-WTB	SVO (59.3%)	SVO (64.8%)	+5.5%
	OLD CHURCH SLAVONIC-PROIEL	SVO (52.0%)	SVO (57.4%)	+5.5%
	CZECH-FICTREE	SVO (47.6%)	SVO (52.7%)	+5.1%

Table 5 :

 5 Corpora for which the first rank difference with or without isubj is greater than 5% (in bold, the corpus for which the first rank changes).

See: https://wals.info/author.

Greenberg's universals are 45 linguistic universals dealing with basic word order, morphology and syntax based on

languages[START_REF] Joseph | Some universals of grammar with particular reference to the order of meaningful elements[END_REF].

See: https://universaldependencies.org/ u/overview/enhanced-syntax.html.

At the time of writing, DUD annotations are not available for version 2.7.

This is a limitation, in particular for some languages like French with impersonal redistribution.

See: http://match.grew.fr/.

A limitation of our experiment is that we cannot take into account cases in which the pronoun is not explicit (in pro-drop languages).

Note that, with the new annotations, we obtain a graph.

We are aware that WALS andÖstling (2015) classifications only deal with transitive clauses, however the UD annotations do not allow us to extract them precisely.

11 See: https://wals.info/feature/81A.

https://gitlab.inria.fr/ud-greenberg/ ranlp-2021

https://olki.loria.fr/

Acknowledgements

We thank the reviewers for their useful remarks. We also wish to thank the colleagues who kindly took the time to answer our questions concerning some of the results we obtained in languages we do not speak: Sashi Narayan and Lydie Lemoine for Hindi, Hilda Mock for Arabic, Kim Gerdes for German and Vincent Vandeghinste for Dutch. The internship of the first author, during which this work has been done, was funded by the Lorraine Université d'Excellence OLKI research project 13 .