Triple
T37013395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2024 NCAA Division I women’s basketball tournament |
E916008
|
entity |
| Predicate | languageMajorCoverage |
P38135
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [2024 NCAA Division I women’s basketball tournament, languageMajorCoverage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageMajorCoverage Context triple: [2024 NCAA Division I women’s basketball tournament, languageMajorCoverage, English]
-
A.
languageOfCoverage
chosen
Indicates the language in which the coverage, such as reporting or documentation about something, is expressed.
-
B.
languageFamilyCoverage
Indicates the extent to which a given entity (such as a resource, model, or system) supports or covers the languages within a specified language family.
-
C.
shareMajorLanguage
Indicates that the entities have at least one primary or major language in common.
-
D.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
E.
numberOfMajorLanguages
Indicates the total count of major languages associated with a given entity.
- 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_69f76e90ed548190b187d2475f5c807d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a016336c58081909c58c5772e6fb488 |
completed | May 11, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_6a0160f25d8081909a6aaa375e9850b0 |
completed | May 11, 2026, 4:54 a.m. |
Created at: May 3, 2026, 4:14 p.m.