Corpus Anotation

• Manual tokeniation & spelling correction
• Parse trees from Bikel parser
• difficult decisions documented
• Two passes

Parser

Baseline parse: Berkley parser (split/merge). 5th order grammar. POS tagging is done by the grammar.

Experiments

• untokenized w/ spelling errors: F=69.6
• gold tokenization w/ spelling errors: F=72.4 (+2.8) - missing apostraphes (eg didnt) cause issues
• gold tokenization w/ spelling corrected: 74.75 (+2.35) - mis-spelled function words cause significant problems. e.g. "whpo"

Issues for the parer

• Subject ellipsis
• adjective/adverb switch (eg use "bad" rather than "badly")
• unseen acronyms (lol)
• abbreviations (cos=because)
• non-standard capitalization (eg all-caps, missing caps)
• unknown idioms (eg "spot on.")
• run-on sentences

Improving Performance

Transform test:

• Fix caps, expand abbreviations, remove interjections (lol), etc.

Transform dev set: retrain the parser with modifications to portions of the training data:

• proper nouns uncapitlized
• -ly removed from adverbs

Self-training/co-training experiments

Try using a different corpus for training (eg Brown, switchboard)

Trying parsing with multiple grammars