Triple
T17569305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BidirectionalCollection |
E427892
|
entity |
| Predicate | languageFeatureCategory |
P51750
|
FINISHED |
| Object | Generics |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Generics | Statement: [BidirectionalCollection, languageFeatureCategory, Generics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageFeatureCategory Context triple: [BidirectionalCollection, languageFeatureCategory, Generics]
-
A.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
B.
languageCore
Indicates a fundamental or primary language associated with or used by an entity.
-
C.
languageParadigm
Indicates a relationship where a programming language follows, supports, or is categorized under a particular programming paradigm.
-
D.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
E.
programmingFeature
chosen
Indicates a relationship where one entity is a specific programming-related capability, construct, or functionality provided or supported by another entity (such as a language, tool, or system).
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4592f29d08190bc3de905d35af849 |
completed | April 19, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.