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Morphological Features for Parsing Morphologically-rich Languages: A Case of Arabic

What it is about

Dehdari, Tounsi and van Genabith ask which morphological features, folded into the POS tag, help a PCFG latent-annotation parser (a re-implemented Berkeley parser) on the Penn Arabic Treebank, using the ATB3-v3.2 80/10/10 split. Of the 498 full ATB tags, they identify 15 features that can be included or excluded, giving 32,768 combinations, too many to try all. They compare non-iterative search, greedy search, a merged heuristic, best-first search with backtracking, and simulated annealing (mean dev F 82.84, standard deviation 0.21 over 50 runs). Backtracking finds the best set: genitive clitics, proper noun, negation and determiner. The conclusion reports F 85.03 for vocalized and 83.34 for unvocalized no-tag parsing, with product models and unknown-word signature classes. Case helped gold parsing but not predicted parsing, and the authors conclude that no tagset is best for every task.

Ideas

For Mova

I1 is an experiment plan for tools/hbo and gparse, to be run on dev before any claim. I2 goes into the unknown-word handling of tools/hbo (unpointed mode) and into The Noun, the Adjective and the Numeral. I3 is the ordering rule for the search in I1.

Cite

The paper itself, not this card. BibTeX from the library's record of the work.

@inproceedings{dehdari2011morphological,
  title = {{Morphological Features for Parsing Morphologically-rich Languages: A Case of Arabic}},
  author = {Dehdari, Jon and Tounsi, Lamia and Genabith, Josef van},
  booktitle = {Proceedings of the Second Workshop on Statistical Parsing of Morphologically Rich Languages},
  year = {2011},
  url = {https://aclanthology.org/W11-3802/}
}

References

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