Bilingual FrameNet Dictionaries for Machine Translation
Summary
The paper sets out the design of GermanFrameNet (GFN), a planned German lexical resource modeled on the English FrameNet built at ICSI Berkeley. Its motivation is that machine translation needs more than word-to-word correspondences: it must know how a shared meaning is expressed syntactically in each language. Grounded in Frame Semantics (Fillmore, 1982), GFN aims to build corpus-based entries for several thousand German verbs, nouns and adjectives. Each lexical unit records its frame elements and the phrase types and grammatical functions realizing them, supported by annotated corpus sentences.
The work runs in two phases. First, German fragments are created to mirror existing English FrameNet fragments, testing whether English-derived frames carry over to German. Second, the two lexicons are connected via shared frames and numerical indices to form a bilingual dictionary. Using the Communication-Statement frame as its example, the author argues for splitting senses by frame, a finer-grained treatment of polysemy than EuroWordNet's. No experiments are reported. The contribution is a resource design meant to help identify the closest translation equivalent.
Key points
- GFN targets several thousand German lexical units (verbs, nouns, adjectives) across multiple semantic domains, following the FrameNet database structure.
- English FrameNet entries combine a frame, the syntactic realizations of its frame elements (e.g., NP.Ext, PP_by.Comp, CNI/DNI/INI null instantiation), annotated example sentences, and relations to other frames. The British National Corpus is FrameNet's main corpus.
- The Communication-Statement frame (Speaker, Addressee, Message, Topic) serves as the worked example, with verbs such as announce, admit, mention, tell and talk, and nouns such as announcement.
- Cross-lingual linking relies on common semantic frames plus numerical indexing of individual senses.
- GFN is framed as a lexicographic, contrastive database rather than an NLP system, with machine translation as the main intended application.
Cited by
- Probabilistic Frame-Semantic Parsing
- Semi-Supervised Frame-Semantic Parsing for Unknown Predicates
- Frame-Semantic Parsing
- BiFrameNet: Bilingual Frame Semantics Resource Construction by Cross-lingual Induction
Cite
@inproceedings{boas2002bilingual,
title = {{Bilingual FrameNet Dictionaries for Machine Translation}},
author = {Boas, Hans C.},
booktitle = {Proceedings of the Third International Conference on Language Resources and Evaluation (LREC'02)},
year = {2002},
doi = {10.63317/4otx22fqqe89},
url = {https://doi.org/10.63317/4otx22fqqe89}
}References
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