AutoSlog System
Jump to navigation
Jump to search
An AutoSlog System is an text-based information extraction algorithm that automatically built dictionaries based on slot-filling rules in a manner that is similar to the one proposed in (Riloff, 1993).
- Context:
- It was trained on an Annotated Corpus.
- It used simple linguistic Rules.
- See: Extraction-Rule Learning.
References
2009
- TBD
- Used a corpus of answer keys and texts from MUC-4 to compare filled templates with the sentences they were taken from.
- Compared a sentence's linguistic parse to a set of heuristic linguistic patterns
- Built a syntactic pattern to extract noun phrases similar to the slotfillers from the template.
- Given the slot-filler "bombed", for example, Auto-Slog might find a sentence with the phrase "public buildings were bombed" and associate the pattern <subject> passive-verb with it, extracting "public buildings" as a dictionary term.
1993
- (Riloff, 2003) ⇒ Ellen Riloff (1993). “Automatically Constructing a Dictionary for Information Extraction Tasks.” In: Proceedings of AAAI-93.