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user:zeman:treebanks:et [2011/11/21 13:26]
zeman Obtaining, license, references and domain. 		user:zeman:treebanks:et [2011/11/28 17:10] (current)
zeman New training/test data split.
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 The EKP is freely [[http://vvv.cs.ut.ee/~kaili/Korpus/puud/|downloadable from here]] in [[http://beta.visl.sdu.dk/treebanks.html#The_source_format|VISL]] or [[http://www.ims.uni-stuttgart.de/projekte/TIGER/TIGERSearch/doc/html/TigerXML.html|TIGER-XML]] format. Licensing terms are unknown. The EKP is freely [[http://vvv.cs.ut.ee/~kaili/Korpus/puud/|downloadable from here]] in [[http://beta.visl.sdu.dk/treebanks.html#The_source_format|VISL]] or [[http://www.ims.uni-stuttgart.de/projekte/TIGER/TIGERSearch/doc/html/TigerXML.html|TIGER-XML]] format. Licensing terms are unknown.
  
-EKP was created / coordinated (?) by Kaili Müürisep, [[http://www.cs.ut.ee/|Institute of Computer Science]] (Arvutiteadus Tartu Ülikoolis), University of Tartu, Liivi 2, 50409 Tartu, Estonia.+EKP was created / coordinated (?) by Kaili Müürisep, [[http://www.cs.ut.ee/|Institute of Computer Science]] (Arvutiteaduse instituut), University of Tartu (Tartu Ülikool), Liivi 2, 50409 Tartu, Estonia.
  
 ==== References ==== ==== References ====
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 ==== Size ==== ==== Size ====
  
-According to their website, the TIGER Treebank version 1 contains approximately 700,000 tokens in 40,000 sentences. Version 2.1 contains approximately 900,000 tokens in 50,000 sentences.+All four parts of the treebank together contain 9491 tokens in 1315 sentences, yielding 7.22 tokens per sentence on average. No official training-test data split is defined. Due to the small size of the treebank and extraordinary domain diversity, a good test set should sample from all four parts of the treebank. This is the case of our HamleDT experimental data split, shown in the last two rows of the table.
  
-The CoNLL 2006 version contains 705,304 tokens in 39573 sentences, yielding 17.82 tokens per sentence on average (CoNLL 2006 data split: 699,610 tokens / 39216 sentences training, 5694 tokens / 357 sentences test). +^ File ^ Sentences ^ Terminals ^ Average t/s ^ 
- +| arborest.xml |  175 |  2451 |  14.01 | 
-The CoNLL 2009 version contains 712,332 tokens in 40020 sentences, yielding 17.80 tokens per sentence on average (CoNLL 2009 data split: 648,677 tokens / 36020 sentences training, 32033 tokens / 2000 sentences development, 31622 tokens / 2000 sentences test).+| piialaused.xml |  732 |  4505 |  6.15 | 
 +| ratsepalaused.xml |  388 |  2348 |  6.05 | 
 +| sul.xml |  20 |  187 |  9.35 | 
 +| **total** |  **1315** |  **9491** |  **7.22** | 
 +| training |  1184 |  8535 |  7.21 | 
 +| test |  131 |  956 |  7.30 |
  
 ==== Inside ==== ==== Inside ====
  
-The treebank is part of the [[http://corp.hum.sdu.dk/tgrepeye_est.html|Arborest]] project and [[http://beta.visl.sdu.dk/|VISL]] (Visual Interactive Syntax Learning). As such, it is based on Constraint Grammar (Fred Karlsson et al., 1995: Constraint Grammar – A Language-Independent System for Parsing Unrestricted Text. Mouton de Gruyter).+The treebank is part of the [[http://corp.hum.sdu.dk/tgrepeye_est.html|Arborest]] project and [[http://beta.visl.sdu.dk/|VISL]] (Visual Interactive Syntax Learning). As such, it is based on Constraint Grammar (Fred Karlsson et al., 1995: Constraint Grammar – A Language-Independent System for Parsing Unrestricted Text. Mouton de Gruyter). All four parts are available in the [[http://www.ims.uni-stuttgart.de/projekte/TIGER/TIGERSearch/doc/html/TigerXML.html|TIGER-XML]] format. Two of them are also available in the [[http://beta.visl.sdu.dk/treebanks.html#The_source_format|VISL]] format.
  
-All versions contain //semi-automatic// part of speech tags ([[http://www.ims.uni-stuttgart.de/projekte/corplex/TagSets/stts-table.html|Stuttgart-Tübingen Tagset]], STTS) and syntactic structure. Lemmas and morphosyntactic features are available only for newer versions (TIGER Treebank version 2 and onwards, and CoNLL 2009). The parts of speech are heavily context-dependent, e.g. many words can be used both substantively (pronouns) and attributively (determiners), which is distinguished by different POS tags.+The annotation contains lemmas, part of speech tags, morphosyntactic features, nonterminal labels and phrase structure. It is not clear whether (and to what degree) the annotation was performed or checked manually.
  
-It is not clear what the //semi-automatic// annotation means (probably first auto-tagging, then manual correction?) and whether it also applies to the morphosyntactic annotation. The CoNLL 2009 version also contains automatically disambiguated lemmas, tags and features. +Note that the TIGER-XML format, despite being phrase-based, stores word order separately from structure and thus allows for nonprojectivities.
- +
-The original treebank is phrase-based. The dependencies in the CoNLL versions must have thus been drawn using a head-selection procedure. Besides CoNLL data, the TIGER project also provides a subset of the TIGER Treebank in a dependency format.+
  
 ==== Sample ==== ==== Sample ====
  
-The first sentence of TIGER Treebank 2.1 in the TIGER-XML format:+The first sentence of the corpus in the TIGER-XML format:
  
-<code xml><s id="s1"> +<code xml><s id="ratsep-13" ref="ratsep-1" source="id=ratsep-1" forest="1/1" text="Peeter aerutas üle väina saarele puhkama"> 
-  <graph root="s1_VROOT"> + <graph root="ratsep-13_501"> 
-    <terminals> + <terminals> 
-      <t id="s1_1" word="``" lemma="--" pos="$(" morph="--" case="--" number="--" gender="--" person="--" degree="--" tense="--" mood="--" /> + <t id="ratsep-13_1" word="Peeter" lemma="Peeter+0" pos="prop" morph="prop,sg,nom,.cap"/> 
-      <t id="s1_2" word="Ross" lemma="Ross" pos="NE" morph="Nom.Sg.Masc" case="Nom" number="Sg" gender="Masc" person="--" degree="--" tense="--" mood="--" /> + <t id="ratsep-13_2" word="aerutas" lemma="aeruta+s" pos="v-fin" morph="main,indic,impf,ps3,sg,ps,af,.FinV"/> 
-      <t id="s1_3" word="Perot" lemma="Perot" pos="NE" morph="Nom.Sg.Masc" case="Nom" number="Sg" gender="Masc" person="--" degree="--" tense="--" mood="--" /> + <t id="ratsep-13_3" word="üle" lemma="üle+0" pos="prp" morph="pre,.gen"/> 
-      <t id="s1_4" word="wäre" lemma="sein" pos="VAFIN" morph="3.Sg.Past.Subj" case="--" number="Sg" gender="--" person="3" degree="--" tense="Past" mood="Subj" /> + <t id="ratsep-13_4" word="väina" lemma="väin+0" pos="n" morph="com,sg,gen"/> 
-      <t id="s1_5" word="vielleicht" lemma="vielleicht" pos="ADV" morph="--" case="--" number="--" gender="--" person="--" degree="--" tense="--" mood="--" /> + <t id="ratsep-13_5" word="saarele" lemma="saar+le" pos="n" morph="com,sg,all"/> 
-      <t id="s1_6" word="ein" lemma="ein" pos="ART" morph="Nom.Sg.Masc" case="Nom" number="Sg" gender="Masc" person="--" degree="--" tense="--" mood="--" /> + <t id="ratsep-13_6" word="puhkama" lemma="puhka+ma" pos="v-inf" morph="main,sup,ps,ill,.Part"/> 
-      <t id="s1_7" word="prächtiger" lemma="prächtig" pos="ADJA" morph="Pos.Nom.Sg.Masc" case="Nom" number="Sg" gender="Masc" person="--" degree="Pos" tense="--" mood="--" /> + <t id="ratsep-13_7" word="." lemma="." pos="punc" morph="Fst"/> 
-      <t id="s1_8" word="Diktator" lemma="Diktator" pos="NN" morph="Nom.Sg.Masc" case="Nom" number="Sg" gender="Masc" person="--" degree="--" tense="--" mood="--" /> + </terminals> 
-      <t id="s1_9" word="''" lemma="--" pos="$(" morph="--" case="--" number="--" gender="--" person="--" degree="--" tense="--" mood="--" /> + 
-    </terminals> + <nonterminals> 
-    <nonterminals> + <nt id="ratsep-13_501" cat="VROOT"> 
-      <nt id="s1_500" cat="PN"> + <edge label="STA" idref="ratsep-13_502"/> 
-        <edge label="PNC" idref="s1_2" /> + </nt> 
-        <edge label="PNC" idref="s1_3" /> + <nt id="ratsep-13_502" cat="fcl"> 
-      </nt> + <edge label="S" idref="ratsep-13_1"/> 
-      <nt id="s1_501" cat="NP"> + <edge label="P" idref="ratsep-13_2"/> 
-        <edge label="NK" idref="s1_6" /> + <edge label="A" idref="ratsep-13_503"/> 
-        <edge label="NK" idref="s1_7" /> + <edge label="A" idref="ratsep-13_5"/> 
-        <edge label="NK" idref="s1_8" /> + <edge label="A" idref="ratsep-13_6"/> 
-      </nt> + <edge label="FST" idref="ratsep-13_7"/> 
-      <nt id="s1_502" cat="S"> + </nt> 
-        <edge label="SB" idref="s1_500" /> + <nt id="ratsep-13_503" cat="pp"> 
-        <edge label="HD" idref="s1_4" /> + <edge label="H" idref="ratsep-13_3"/> 
-        <edge label="MO" idref="s1_5" /> + <edge label="D" idref="ratsep-13_4"/> 
-        <edge label="PD" idref="s1_501" /> + </nt> 
-      </nt> + </nonterminals> 
-      <nt id="s1_VROOT" cat="VROOT"> + </graph>
-        <edge label="--" idref="s1_1" /> +
-        <edge label="--" idref="s1_502" /> +
-        <edge label="--" idref="s1_9" /> +
-      </nt> +
-    </nonterminals> +
-  </graph>+
 </s></code> </s></code>
- 
-The first sentence of the CoNLL 2006 training data: 
- 
-| 1 | `` | _ | $( | $( | _ | 4 | PUNC | 4 | PUNC | 
-| 2 | Ross | _ | NE | NE | _ | 4 | SB | 4 | SB | 
-| 3 | Perot | _ | NE | NE | _ | 2 | PNC | 2 | PNC | 
-| 4 | wäre | _ | VAFIN | VAFIN | _ | 0 | ROOT | 0 | ROOT | 
-| 5 | vielleicht | _ | ADV | ADV | _ | 4 | MO | 4 | MO | 
-| 6 | ein | _ | ART | ART | _ | 8 | NK | 8 | NK | 
-| 7 | prächtiger | _ | ADJA | ADJA | _ | 8 | NK | 8 | NK | 
-| 8 | Diktator | _ | NN | NN | _ | 4 | PD | 4 | PD | 
-| 9 | <nowiki>''</nowiki> | _ | $( | $( | _ | 4 | PUNC | 4 | PUNC | 
- 
-The first sentence of the CoNLL 2006 test data: 
- 
-| 1 | Zwei | _ | CARD | CARD | _ | 2 | NK | 2 | NK | 
-| 2 | Themen | _ | NN | NN | _ | 14 | SB | 14 | SB | 
-| 3 | , | _ | $, | $, | _ | 2 | PUNC | 2 | PUNC | 
-| 4 | die | _ | PRELS | PRELS | _ | 8 | OA | 8 | OA | 
-| 5 | Perot | _ | NE | NE | _ | 8 | SB | 8 | SB | 
-| 6 | immer | _ | ADV | ADV | _ | 7 | MO | 7 | MO | 
-| 7 | wieder | _ | ADV | ADV | _ | 8 | MO | 8 | MO | 
-| 8 | anspricht | _ | VVFIN | VVFIN | _ | 2 | RC | 2 | RC | 
-| 9 | , | _ | $, | $, | _ | 2 | PUNC | 2 | PUNC | 
-| 10 | Rezession | _ | NN | NN | _ | 2 | APP | 2 | APP | 
-| 11 | und | _ | KON | KON | _ | 10 | CD | 10 | CD | 
-| 12 | Bürokratie | _ | NN | NN | _ | 10 | CJ | 10 | CJ | 
-| 13 | , | _ | $, | $, | _ | 14 | PUNC | 14 | PUNC | 
-| 14 | machen | _ | VVFIN | VVFIN | _ | 0 | ROOT | 0 | ROOT | 
-| 15 | ihnen | _ | PPER | PPER | _ | 18 | DA | 18 | DA | 
-| 16 | besonders | _ | ADV | ADV | _ | 18 | MO | 18 | MO | 
-| 17 | zu | _ | PTKZU | PTKZU | _ | 18 | PM | 18 | PM | 
-| 18 | schaffen | _ | VVINF | VVINF | _ | 14 | OC | 14 | OC | 
-| 19 | . | _ | $. | $. | _ | 14 | PUNC | 14 | PUNC | 
- 
-The first sentence of the CoNLL 2009 training data: 
- 
-| 1 | `` | _ | `` | $( | $( | _ | _ | 4 | 4 | PUNC | PUNC | _ | _ | 
-| 2 | Ross | Ross | Roß | NE | NN | Nom<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Masc | _ | 3 | 3 | PNC | PNC | _ | _ | 
-| 3 | Perot | Perot | Perot | NE | NE | Nom<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Masc | _ | 4 | 4 | SB | SB | _ | _ | 
-| 4 | wäre | sein | sein | VAFIN | VAFIN | 3<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Past<nowiki>|</nowiki>Subj | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Past<nowiki>|</nowiki>Subj | 0 | 0 | ROOT | ROOT | _ | _ | 
-| 5 | vielleicht | vielleicht | vielleicht | ADV | ADV | _ | _ | 4 | 4 | MO | MO | _ | _ | 
-| 6 | ein | ein | ein | ART | ART | Nom<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Masc | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>* | 8 | 8 | NK | NK | _ | _ | 
-| 7 | prächtiger | prächtig | prächtig | ADJA | ADJA | Pos<nowiki>|</nowiki>Nom<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Masc | *<nowiki>|</nowiki>*<nowiki>|</nowiki>*<nowiki>|</nowiki>* | 8 | 8 | NK | NK | _ | _ | 
-| 8 | Diktator | Diktator | Diktator | NN | NN | Nom<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Masc | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Masc | 4 | 4 | PD | PD | _ | _ | 
-| 9 | <nowiki>''</nowiki> | _ | <nowiki>''</nowiki> | $( | $( | _ | _ | 4 | 4 | PUNC | PUNC | _ | _ | 
- 
-The first sentence of the CoNLL 2009 development data: 
- 
-| 1 | Maschinenbau | Maschinenbau | Maschinenbau | NN | NN | Nom<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Masc | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Masc | 0 | 4 | ROOT | NK | _ | _ | 
-| 2 | / | _ | / | $( | $( | _ | _ | 0 | 1 | PUNC | PUNC | _ | _ | 
-| 3 | ( | _ | ( | $( | $( | _ | _ | 0 | 4 | PUNC | PUNC | _ | _ | 
-| 4 | Zusammenfassung | Zusammenfassung | Zusammenfassung | NN | NN | Nom<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | 0 | 0 | ROOT | ROOT | _ | _ | 
-| 5 | ) | _ | ) | $( | $( | _ | _ | 0 | 1 | PUNC | PUNC | _ | _ | 
- 
-The first sentence of the CoNLL 2009 test data: 
- 
-| 1 | Gegen | gegen | gegen | APPR | APPR | _ | _ | _ | _ | _ | _ | _ | 
-| 2 | eine | ein | ein | ART | ART | Acc<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | _ | _ | _ | _ | _ | 
-| 3 | Erweiterung | Erweiterung | Erweiterung | NN | NN | Acc<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | _ | _ | _ | _ | _ | 
-| 4 | ihrer | ihr | ihr | PPOSAT | PPOSAT | Gen<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | *<nowiki>|</nowiki>*<nowiki>|</nowiki>* | _ | _ | _ | _ | _ | 
-| 5 | Organisation | Organisation | Organisation | NN | NN | Gen<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | _ | _ | _ | _ | _ | 
-| 6 | zu | zu | zu | APPR | APPR | _ | _ | _ | _ | _ | _ | _ | 
-| 7 | einem | ein | ein | ART | ART | Dat<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Neut | Dat<nowiki>|</nowiki>Sg<nowiki>|</nowiki>* | _ | _ | _ | _ | _ | 
-| 8 | sicherheitspolitischen | sicherheitspolitisch | sicherheitspolitisch | ADJA | ADJA | Pos<nowiki>|</nowiki>Dat<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Neut | Pos<nowiki>|</nowiki>*<nowiki>|</nowiki>*<nowiki>|</nowiki>* | _ | _ | _ | _ | _ | 
-| 9 | Forum | Forum | Forum | NN | NN | Dat<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Neut | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Neut | _ | _ | _ | _ | _ | 
-| 10 | sprachen | sprechen | sprechen | VVFIN | VVFIN | 3<nowiki>|</nowiki>Pl<nowiki>|</nowiki>Past<nowiki>|</nowiki>Ind | *<nowiki>|</nowiki>Pl<nowiki>|</nowiki>Past<nowiki>|</nowiki>Ind | _ | _ | _ | _ | Y | 
-| 11 | sich | sich | er<nowiki>|</nowiki>es<nowiki>|</nowiki>sie<nowiki>|</nowiki>Sie | PRF | PRF | 3<nowiki>|</nowiki>Acc<nowiki>|</nowiki>Pl | *<nowiki>|</nowiki>*<nowiki>|</nowiki>* | _ | _ | _ | _ | _ | 
-| 12 | die | der | d | ART | ART | Nom<nowiki>|</nowiki>Pl<nowiki>|</nowiki>Masc | *<nowiki>|</nowiki>*<nowiki>|</nowiki>* | _ | _ | _ | _ | _ | 
-| 13 | meisten | meister | meist | PIAT | PIAT | Nom<nowiki>|</nowiki>Pl<nowiki>|</nowiki>Masc | *<nowiki>|</nowiki>*<nowiki>|</nowiki>* | _ | _ | _ | _ | _ | 
-| 14 | Staaten | Staat | Staat | NN | NN | Nom<nowiki>|</nowiki>Pl<nowiki>|</nowiki>Masc | *<nowiki>|</nowiki>Pl<nowiki>|</nowiki>Masc | _ | _ | _ | _ | _ | 
-| 15 | beim | bei | beim | APPRART | APPRART | Dat<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Neut | Dat<nowiki>|</nowiki>Sg<nowiki>|</nowiki>* | _ | _ | _ | _ | _ | 
-| 16 | Gipfeltreffen | Gipfeltreffen | Gipfeltreffen | NN | NN | Dat<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Neut | *<nowiki>|</nowiki>*<nowiki>|</nowiki>Neut | _ | _ | _ | _ | _ | 
-| 17 | für | für | für | APPR | APPR | _ | _ | _ | _ | _ | _ | _ | 
-| 18 | Asiatisch-Pazifische | asiatisch-pazifisch | Asiatisch-Pazifische | ADJA | NN | Pos<nowiki>|</nowiki>Acc<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | *<nowiki>|</nowiki>*<nowiki>|</nowiki>* | _ | _ | _ | _ | _ | 
-| 19 | Wirtschaftskooperation | Wirtschaftskooperation | Wirtschaftskooperation | NN | NN | Acc<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | _ | _ | _ | _ | _ | 
-| 20 | ( | _ | ( | $( | $( | _ | _ | _ | _ | _ | _ | _ | 
-| 21 | Apec | Apec | _ | NE | NE | Nom<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Fem | _ | _ | _ | _ | _ | _ | 
-| 22 | ) | _ | ) | $( | $( | _ | _ | _ | _ | _ | _ | _ | 
-| 23 | in | in | in | APPR | APPR | _ | _ | _ | _ | _ | _ | _ | 
-| 24 | Osaka | Osaka | Osaka | NE | NE | Dat<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Neut | *<nowiki>|</nowiki>Sg<nowiki>|</nowiki>Neut | _ | _ | _ | _ | _ | 
-| 25 | aus | aus | aus | PTKVZ | PTKVZ | _ | _ | _ | _ | _ | _ | _ | 
-| 26 | . | _ | . | $. | $. | _ | _ | _ | _ | _ | _ | _ | 
  
 ==== Parsing ==== ==== Parsing ====
  
-TIGER is a mildly nonprojective treebank. 15875 of the 680,710 tokens in the CoNLL 2009 training+development datasets are attached nonprojectively (2.33%). +Nonprojectivities in EKP are very rare. Only 7 out of the 9491 tokens are attached nonprojectively (0.074%).
- +
-The results of the CoNLL 2006 shared task are [[http://ilk.uvt.nl/conll/results.html|available online]]. They have been published in [[http://aclweb.org/anthology-new/W/W06/W06-2920.pdf|(Buchholz and Marsi, 2006)]]. The evaluation procedure was non-standard because it excluded punctuation tokens. These are the best results for German: +
- +
-^ Parser (Authors) ^ LAS ^ UAS ^ +
-| MST (McDonald et al.) | 87.34 | 90.38 | +
-| Riedel et al. | 86.24 | 89.76 | +
-| Basis (O'Neil) | 85.36 | 89.16 | +
-| Malt (Nivre et al.) | 85.82 | 88.76 | +
- +
-The results of the CoNLL 2009 shared task are [[http://ufal.mff.cuni.cz/conll2009-st/results/results.php|available online]]. They have been published in [[http://aclweb.org/anthology/W/W09/W09-1201.pdf|(Hajič et al., 2009)]]. Unlabeled attachment score was not published. These are the best results for German:+
  
-^ Parser (Authors) ^ LAS ^ +There is a constraint grammar parser for Estonian by Kaili Müürisep. I am not aware of any published evaluation of parsing accuracy. However, I am not sure that the treebank described here is not just output of the parser.
-| Bohnet | 87.48 | +
-| Merlo | 87.29 | +
-| Chen | 86.24 | +
-| Che | 86.19 |+
  

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