A sense-based lexicon of count and mass expressions: The Bochum English Countability Lexicon
Bibliographic record
Abstract
The present paper describes the current release of the Bochum English Countability Lexicon (BECL 2.1), a large empirical database consisting of lemmata from Open ANC (http://www.anc.org) with added senses from WordNet (Fellbaum, 1998).BECL 2.1 contains ≈ 11,800 annotated noun-sense pairs, divided into four major countability classes and 18 fine-grained subclasses.In the current version, BECL also provides information on nouns whose senses occur in more than one class allowing a closer look on polysemy and homonymy with regard to countability.Further included are sets of similar senses using the Leacock and Chodorow (LCH) score for semantic similarity (Leacock & Chodorow, 1998), information on orthographic variation, on the completeness of all WordNet senses in the database and an annotated representation of different types of proper names.The further development of BECL will investigate the different countability classes of proper names and the general relation between semantic similarity and countability as well as recurring syntactic patterns for noun-sense pairs.Our current work on those patterns concerning mass nouns is briefly discussed pointing to further research.The BECL 2.1 database is also publicly available via http://count-and-mass.org.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".