Gold standard corpus annotated with verb-preverb connections for Hungarian.

Overview

Hungarian Preverb Corpus

A gold standard corpus manually annotated with verb-preverb connections for Hungarian.

corpus

The corpus consist of the following 4 files:

filename # sentences # preverbs
difficult_validate1.txt 310 357
difficult_validate2.txt 840 935
difficult_test.txt 327 376
general_test.txt 503 500

Preverbs in the general dataset are in the distribution as they appear in normal Hungarian text. The difficult dataset is specially crafted: the most common and most-easy-to-handle pattern, i.e. when a verb is directly followed by its preverb (e.g. megy ki 'go out'), is omitted. validate is for development/validation, test is for testing. Note that a general_validate dataset would not be useful, because the trivial pattern would be in vast majority overwhelming the more interesting less frequent patterns.

Accordingly, the emPreverb tool which connects preverbs to their corresponding verb, was developed based only on interesting difficult examples, and tested both on difficult and general data.

(Remark. The difficult_validate dataset is divided into two parts for historical reasons, but you can simply use them together: they consist a total of 1150 sentences and 1292 preverbs.)

corpus annotation guidelines

  • Preverb marked by a suffixed backslash followed by a (single digit!) ID number: meg\1.
  • Word from which the preverb was separated marked by a pipe followed by the same ID number: főzve|1.
  • Within the same line, different verb-prefix pairs must (obviously) receive different ID numbers.
  • A preverb that does not belong to any word in the sentence (ellipsis etc.) is marked with a zero ID: "Hazakísérhetlek?" "Meg\0 hát." Any number of preverbs can have the 0 ID within the same line.
  • In the difficult dataset, a verb directly followed by its preverb is not annotated: főzte meg, but: főzte|1 volna meg\1.
  • In the general dataset, the first pattern is annotated as well: főzte|1 meg\1.
  • Normally there is a 1:1 correspondence between preverbs and verbs. However, there are exceptions, and these are annotated accordingly, e.g. Se ki\1, se be\1 nem lehetett menni|1 Budakesziről; át-\1 meg átjárták|1.

Check (see Step 1 to 4 in evaluate.ipynb) whether tokens annotated as separated preverbs are also analysed by e-magyar morph,pos as preverbs. If not (e.g. if the preverb meg is tagged by emtsv as a [/Conj]), remove this annotation (or the whole item if no annotation left) from the dataset because preverb will necessarily fail due to incorrect emtsv annotation, which is extraneous to its performance evaluation. Exception: person-inflected preverb-like postpositions such as in utánam\1 dobják|1, which are tagged by emtsv as [/Post], and case-inflected personal pronouns such as in hozzá\1 voltam szokva|1, which are tagged as [/N|Pro], should not be removed from the dataset since preverb should be able to handle these.

If a token is annotated as the verb stem counterpart of a separated preverb, but is not tagged by emtsv as a verb, check whether the preverb annotation is correct, but if so, do not remove this annotation from the dataset. preverb is supposed to be able to handle the connection of such separated preverbs.

evaluation

An environment for reproducing evaluation of emPreverb as published in the paper below.

git clone https://github.com/ril-lexknowrep/emPreverb
cd emPreverb
make evaluate

Note that make evaluate clones this current repo inside emPreverb and runs evaluation.

The results are obtained in general_test_results.txt and difficult_test_results.txt. This should be exactly the same which can be found in Table 3 of the paper below.

development

An environment used for developing emPreverb. It is "for us" but if you insist to use it:

git clone https://github.com/ril-lexknowrep/emPreverb
cd emPreverb
git clone https://github.com/ril-lexknowrep/hungarian-preverb-corpus
cd hungarian-preverb-corpus/development
jupyter notebook evaluate.ipynb

(Remark. Yes, please clone this repo inside emPreverb.)

citation

If you use the corpus, please cite the following paper.

Pethő, Gergely and Sass, Bálint and Kalivoda, Ágnes and Simon, László and Lipp, Veronika: Igekötő-kapcsolás. In: MSZNY 2022.

Owner
RIL Lexical Knowledge Representation Research Group
RIL Lexical Knowledge Representation Research Group
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