SofiaPreprocessingSIG

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Preprocessing and deep grammars

Lead: Kiril || Participants: Petya, Mike, Angelina, Montse, Yi

0. The focus of the discussion is on how to incorporate shallow parses into deep parsing architectures.

1. Problem: - MaltParser - tried on Bulgarian with partial grammars as input, BUT - not always complete trees can be derived. - only one format CoNLL

2. What to be done? - input to bechosen (POS tagged, lemmatized, chunked or DP parsed...) - degrees of reliability of the various preprocessing steps - degrees of control over the various preprocessing steps - towards Statistical parsong where confidence measures can be used

3. Connection to partial FS (hence - to simplified FS) - language grammar specification - mapping between the grammar and the format, i.e. agreement info for chunks - impact of the new words - impact of sure vs. unsure decisions, made by the various preprocessing steps

4. MaltParser again: - no underspecification is possible now - discrepancies between locality in algorithm and linguistic locality

Example: for German first the topological fields are identified, and then -- HPSG analyses are performed.

5. Should morphology be done outside the grammar?

6. Probabilistic model over an PCFG Grammar. However: hard with a single probabilistic model. Thus: parallel model to HPSG grammar?

7. Towards Robust Unification. This implies degrees of constraints. For example, the INFLECTED+/- can be unified, but not singular and plural.

CONCLUSION: The idea of a hybrid approach; information fusion. Everything in a complex system.