Difference between revisions of "Comparison of part-of-speech tagging systems"

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| Russian || 451 || 10,171 || ?|| 75.63 || 79.52 || [70.49, 72.94] || [74.68, 78.65] || n/a || n/a
 
| Russian || 451 || 10,171 || ?|| 75.63 || 79.52 || [70.49, 72.94] || [74.68, 78.65] || n/a || n/a
 
|-
 
|-
| Kazakh || 403 || 4,348 || ? || 80.25 || 86.13 || [83.55, 86.19] || [83.33, 86.61] || n/a || n/a
+
| Kazakh || 403 || 4,348 || ? || 80.79 || 86.19 || [84.36, 87.79] || [85.56, 88.72] || n/a || n/a
 
|-
 
|-
 
| Portuguese || 119 || 3,823 || ? || 72.54 || 87.34 || [77.10, 87.72] || [84.05, 91.96] || ||
 
| Portuguese || 119 || 3,823 || ? || 72.54 || 87.34 || [77.10, 87.72] || [84.05, 91.96] || ||
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* <code>1st</code>: Selects the first analysis from the morphological analyser
 
* <code>1st</code>: Selects the first analysis from the morphological analyser
 
* <code>CG</code>: Uses the CG (from the monolingual language package in [[languages]]) to preprocess the input.
 
* <code>CG</code>: Uses the CG (from the monolingual language package in [[languages]]) to preprocess the input.
* <code>Unigram</code>: Lexicalised unigram tagger
+
* <code>Unigram</code>: Lexicalised [[unigram tagger]]
 
* <code>apertium-tagger</code>: Uses the bigram HMM tagger included with Apertium.
 
* <code>apertium-tagger</code>: Uses the bigram HMM tagger included with Apertium.
   

Revision as of 15:19, 15 January 2016

Apertium would like to have really good part-of-speech tagging, but in many cases falls below the state-of-the-art (around 97% tagging accuracy). This page intends to collect a comparison of tagging systems in Apertium and give some ideas of what could be done to improve them.

In the following table, the intervals represent the [low, high] values from 10-fold cross validation.

Language Corpus System
Sent Tok Amb 1st CG+1st Unigram CG+Unigram apertium-tagger CG+apertium-tagger
Catalan 1,413 24,144 ? 81.85 83.96 [75.65, 78.46] [87.76, 90.48] [94.16, 96.28] [93.92, 96.16]
Spanish 1,271 21,247 ? 86.18 86.71 [78.20, 80.06] [87.72, 90.27] [90.15, 94.86] [91.84, 93.70]
Serbo-Croatian 1,190 20,128 ? 75.22 79.67 [75.36, 78.79] [75.36, 77.28]
Russian 451 10,171 ? 75.63 79.52 [70.49, 72.94] [74.68, 78.65] n/a n/a
Kazakh 403 4,348 ? 80.79 86.19 [84.36, 87.79] [85.56, 88.72] n/a n/a
Portuguese 119 3,823 ? 72.54 87.34 [77.10, 87.72] [84.05, 91.96]
Swedish 11 239 ? 72.90 73.86 [56.00, 82.97]

Sent = sentences, Tok = tokens, Amb = average ambiguity from the morphological analyser

Systems

  • 1st: Selects the first analysis from the morphological analyser
  • CG: Uses the CG (from the monolingual language package in languages) to preprocess the input.
  • Unigram: Lexicalised unigram tagger
  • apertium-tagger: Uses the bigram HMM tagger included with Apertium.

Corpora

The tagged corpora used in the experiments are found in the monolingual packages in languages, under the texts/ subdirectory.

Todo