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Model Performance

Table of contents


Here we report the performance of Stanza’s pretrained models on all supported languages. Again, performances of models for tokenization, multi-word token (MWT) expansion, lemmatization, part-of-speech (POS) and morphological features tagging and dependency parsing are reported on the Universal Dependencies (UD) treebanks, while performances of the NER models are reported separately.

System Performance on UD Treebanks

In the table below you can find the performance of Stanza’s pretrained UD models. All models are trained and tested with the Universal Dependencies v2.5 treebanks. Note that all scores reported are from an end-to-end evaluation on the official test sets (from raw text to the full CoNLL-U file), and are generated with the CoNLL 2018 UD shared task official evaluation script. For detailed interpretation of these scores and the evaluation scripts we used, please refer to the CoNLL 2018 UD Shared Task Evaluation page. For details on how we handled treebanks with no training data, please refer to our CoNLL 2018 system description paper.

For more detailed results and better viewing experience, please access the results in this Google Spreadsheet.

TreebankTokensSentencesWordsUPOSXPOSUFeatsAllTagsLemmasUASLASCLASMLASBLEX
Macro Avg98.6486.8198.4390.9987.8887.7182.0390.5179.8774.8270.9163.2666.04
UD_Afrikaans-AfriBooms99.7599.6599.7597.5694.2797.0394.2497.4887.5184.4578.5874.775.39
UD_Ancient_Greek-Perseus99.9898.8599.9892.5485.2291.0684.9888.2678.7573.3567.8854.2257.54
UD_Ancient_Greek-PROIEL10051.6510097.3897.7592.0990.9697.4280.3476.3371.3761.2369.23
UD_Arabic-PADT99.9880.4397.8894.8991.7591.8691.5193.2783.2779.3376.2470.5872.79
UD_Armenian-ArmTDP98.9695.2296.5892.4996.5888.1986.9492.2778.1872.4668.560.3965.88
UD_Basque-BDT10010010096.2310093.0991.3496.5286.1982.7681.2973.5678.26
UD_Belarusian-HSE99.3878.2499.3891.9231.3477.7326.3179.4869.2863.8858.4941.8844.05
UD_Bulgarian-BTB99.9397.2799.9398.6896.3597.5995.7597.2993.3790.2186.8483.7183.62
UD_Buryat-BDT96.587.8396.541.8396.533.7226.7752.4530.6113.498.971.663.48
UD_Catalan-AnCora99.9999.8499.9898.7598.6698.2997.7498.4792.8490.5686.2584.0785.31
UD_Chinese-GSD92.8398.892.8389.1288.9392.1188.1892.8372.8869.8266.8163.2666.81
UD_Chinese-GSDSimp92.9299.192.9289.0588.8492.1288.0392.9273.4470.4467.6964.0767.69
UD_Classical_Chinese-Kyoto99.4746.9599.4790.2589.6492.6887.3499.4571.8166.0864.5462.6164.54
UD_Coptic-Scriptorium99.9429.9986.0682.3780.2573.5169.4783.1261.9459.7150.4934.1749.54
UD_Croatian-SET99.9698.1599.9697.8894.8695.3294.2296.6790.2785.5682.4376.3778.78
UD_Czech-CAC99.9910099.9798.7694.7993.5292.659891.789.1986.8480.1484.89
UD_Czech-CLTT99.9310099.8498.9291.8991.9791.2897.4886.6783.3879.3570.777.56
UD_Czech-FicTree99.9798.699.9698.3195.2396.0194.5898.4392.6989.8187.381.9485.42
UD_Czech-PDT99.9794.1499.9798.595.3894.6193.6798.559188.6486.9181.1285.45
UD_Danish-DDT99.9693.5799.9697.7599.9697.3896.4597.3286.8384.1981.277.1378.46
UD_Dutch-Alpino99.9689.9899.9696.3394.7696.2894.1396.9789.5686.4481.2275.7677.8
UD_Dutch-LassySmall99.977.9599.995.9794.8796.2294.0597.5985.3481.9375.5471.9873.49
UD_English-EWT99.0181.1399.0195.495.1296.1193.997.2186.2283.5980.2176.0278.5
UD_English-GUM99.8286.3599.8295.8995.9196.8794.9996.887.0683.5778.4274.6874.97
UD_English-LinES99.9588.4999.9596.8895.1896.7693.1198.3285.8281.9779.0474.4777.31
UD_English-ParTUT99.6810099.5996.1595.8395.2193.9297.4590.3187.3582.5676.1980.53
UD_Estonian-EDT99.9693.3299.9697.1998.0495.7794.4396.0586.6883.8282.4177.6378.32
UD_Estonian-EWT99.267.1499.288.8691.787.1683.4385.6267.2360.0756.2148.3247.38
UD_Finnish-FTB10089.5999.9795.595.1296.5193.9296.1689.0986.3983.879.981.02
UD_Finnish-TDT99.7793.0599.7396.9797.7295.3694.4494.9888.6286.1884.6679.7380.24
UD_French-GSD99.6894.9299.4897.399.4796.7296.0597.6491.3889.0584.3880.382.4
UD_French-ParTUT99.8210099.3796.696.3793.9893.4195.4890.7188.3783.3774.4177.88
UD_French-Sequoia99.988.7999.5898.1999.5897.5896.9498.2590.4788.3484.7181.7783.31
UD_French-Spoken10022.0999.4595.4997.0699.4593.2396.5375.8270.7162.1359.5760.44
UD_Galician-CTG99.8999.1399.3297.2196.9999.1496.7197.9485.2282.6677.2471.1375.96
UD_Galician-TreeGal99.5989.1798.4194.2991.8193.3690.8894.3978.0472.9465.6159.0661.49
UD_German-GSD99.5385.7999.5394.0796.9889.5284.5196.3785.3980.6175.3858.5771.24
UD_German-HDT10097.4110098.0497.9491.7791.3497.4894.9192.5988.7377.2685.63
UD_Gothic-PROIEL10039.7110096.1796.7190.6288.8696.4874.6769.0366.2157.1164.38
UD_Greek-GDT99.8893.1899.8997.8497.8494.9494.3396.4991.1288.7884.127879.48
UD_Hebrew-HTB99.9899.6993.1990.4690.4689.2488.4590.2779.1876.671.0564.5167.79
UD_Hindi-HDTB10099.4410097.5997.0894.0392.1196.6694.891.7488.278.7387.01
UD_Hungarian-Szeged99.879799.8796.0399.8793.7692.9494.2583.6278.8677.1469.4671.87
UD_Indonesian-GSD99.9993.7899.9993.6894.799689.1799.6185.1779.1977.0468.8676.68
UD_Irish-IDT99.7695.9399.7693.992.4378.197591.7982.6574.0366.1142.9859.09
UD_Italian-ISDT99.9198.7699.7698.0197.9197.7297.1198.192.7990.8486.4383.684.23
UD_Italian-ParTUT99.8110099.7797.8297.7697.7996.9497.5792.2490.0184.3981.7782.05
UD_Italian-PoSTWITA99.7163.799.4696.1996.0496.2895.0196.782.6778.2772.268.5570.35
UD_Italian-TWITTIRO99.3452.498.7694.4194.0193.3491.4593.1778.8772.8564.6458.6759.35
UD_Italian-VIT99.9894.9299.4997.2196.2396.7994.9998.0189.3285.8780.2676.1678.61
UD_Japanese-GSD92.6794.5792.6791.1690.8492.6690.8492.0281.280.1671.3969.8571.01
UD_Kazakh-KTB93.4688.5694.1656.2356.142.7336.9652.1244.3325.2120.287.6310.01
UD_Korean-GSD99.8896.6599.8896.1890.1499.668892.6987.2983.5381.3479.2975.31
UD_Korean-Kaist10099.9310095.4586.3110086.3193.0288.4186.3883.9580.6377.57
UD_Kurmanji-MG94.8187.4394.4957.1755.9143.0238.4156.1332.0121.9116.353.845.84
UD_Latin-ITTB99.9980.6699.9998.0995.3896.4393.898.987.6185.3684.2380.2883.6
UD_Latin-Perseus10098.2410090.6378.4282.4277.7483.0871.9461.9957.8945.2847.28
UD_Latin-PROIEL10043.0410096.9297.191.2490.3296.7876.5572.3770.0661.2868.19
UD_Latvian-LVTB99.8299.0199.8296.0388.2593.4687.7395.5587.8484.4482.1673.9178.25
UD_Lithuanian-ALKSNIS99.8788.7999.8793.3785.6787.8484.8492.5178.5473.1170.6660.8165.53
UD_Lithuanian-HSE97.5351.1197.5381.0880.0470.7266.4476.948.137.4532.3721.124.86
UD_Livvi-KKPP90.8265.1690.8238.9136.2327.7822.4141.2524.6110.045.140.620.92
UD_Maltese-MUDT99.8684.9499.8695.7595.6399.8695.3199.8683.3178.1570.6467.1570.64
UD_Marathi-UFAL9876.492.2577.2492.2560.2758.5575.7766.4252.6442.824.1533.9
UD_North_Sami-Giella99.6899.3199.6891.1192.8587.7283.888.7974.2268.4365.5958.3258.13
UD_Norwegian-Nynorsk99.9794.8599.9797.9299.9796.8896.0397.991.8789.7387.2882.8684.78
UD_Norwegian-NynorskLIA10099.6910095.9210094.8292.797.7277.8272.9467.5661.3265.54
UD_Norwegian-Bokmaal99.9997.1799.9998.2999.9997.1796.4198.3692.5790.6988.3284.4186.33
UD_Old_Church_Slavonic-PROIEL10049.2610096.5896.8890.6589.6395.6979.7574.9374.6465.4572.02
UD_Old_French-SRCMF10010010096.0596.0997.7495.5610091.3886.3583.3980.0583.39
UD_Old_Russian-TOROT10035.6910093.6393.8386.7684.891.3572.946763.654.1359.18
UD_Persian-Seraji10099.2599.6597.2997.397.3796.8697.7389.4586.0682.788181.08
UD_Polish-LFG99.9599.8399.9598.5594.6695.8494.0796.8695.893.9492.3587.6288.64
UD_Polish-PDB99.8798.3999.8398.3194.0494.2793.1397.2992.6890.488.3581.6985.42
UD_Portuguese-Bosque99.7794.399.6797.0499.6796.3694.9197.890.6787.5782.5976.7880.3
UD_Portuguese-GSD99.969899.8798.1898.1899.7998.1795.8392.8391.3687.4485.8786.75
UD_Romanian-Nonstandard98.9697.5398.9695.490.7389.7988.1994.6387.2482.7177.665.2473.52
UD_Romanian-RRT99.7796.6499.7797.5496.9797.1396.7597.9590.6685.8581.4977.9479.84
UD_Russian-GSD99.6597.1699.6597.3897.1893.1192.2295.3488.9784.8382.3775.1677.75
UD_Russian-SynTagRus99.5798.8699.5798.299.5795.9195.5997.5192.3890.689.0185.0486.78
UD_Russian-Taiga97.1185.7997.1192.2594.785.7682.6189.2872.096661.851.9455.64
UD_Scottish_Gaelic-ARCOSG99.4855.3599.4792.584.8987.9983.9395.5177.970.8162.635459.74
UD_Serbian-SET10099.3310098.4494.2694.5593.8696.3491.7988.7886.579.4882.38
UD_Slovak-SNK99.9790.9399.9796.3487.1591.5986.3494.7389.9686.8284.7475.3979.35
UD_Slovenian-SSJ99.9191.699.9198.2995.0895.3794.5697.3491.6389.687.1882.3584.37
UD_Slovenian-SST10026.5910093.6688.0988.0685.2794.7863.1356.551.3444.8148.96
UD_Spanish-AnCora99.9899.0799.9898.7898.6798.5997.9799.1992.2190.0186.0584.2285.2
UD_Spanish-GSD99.9695.9799.8796.6999.8796.494.4498.4489.6186.7381.2273.9679.19
UD_Swedish_Sign_Language-SSLC1005.8810074.8276.610072.3410023.7611.711.819.4511.81
UD_Swedish-LinES99.9486.9999.9496.9794.5890.1187.3396.7987.183.0680.7667.9777.44
UD_Swedish-Talbanken99.9798.8599.9797.6596.5796.795.6397.5188.9685.9183.5979.1780.78
UD_Tamil-TTB99.5895.0891.4282.678.881.8978.185.1461.2355.7653.4346.449.61
UD_Telugu-MTG10097.9510092.9392.9399.1792.9310089.3279.8974.8871.2574.88
UD_Turkish-IMST99.8997.6298.0794.2193.4392.0890.2794.9270.7864.561.6256.0459.6
UD_Ukrainian-IU99.8196.6599.7996.7792.4992.5391.3196.4987.1183.8680.5173.3877.28
UD_Upper_Sorbian-UFAL89.7279.4589.7258.5789.7238.6436.3952.6434.2523.6117.34.188.62
UD_Urdu-UDTB10098.8810094.4292.6284.2180.3695.6288.382.7877.0659.4874.75
UD_Uyghur-UDT99.7986.999.7989.4591.9287.9280.5496.1675.5563.615746.0654.39
UD_Vietnamese-VTB87.2593.1587.2579.577.987.0277.8787.253.6348.1644.8842.1744.85
UD_Wolof-WTB99.9791.0699.4294.0994.0393.1191.2694.683.2577.0570.9464.2566.99

System Performance on NER Corpora

In the table below you can find the performance of Stanza’s pretrained NER models. All numbers reported are micro-averaged F1 scores. We used canonical train/dev/test splits for all datasets except for the WikiNER datasets, for which we used random splits. The Ukrainian model and its score was provided by a user.

LanguageCorpus# TypesF1
ArabicAQMAR474.3
ChineseOntoNotes1879.2
DutchCoNLL02489.2
DutchWikiNER494.8
EnglishCoNLL03492.1
EnglishOntoNotes1888.8
FrenchWikiNER492.9
GermanCoNLL03481.9
GermanGermEval14485.2
RussianWikiNER492.9
SpanishCoNLL02488.1
SpanishAnCora488.6
Ukrainianlanguk486.05