Triple
T4218556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA Division I women’s track and field teams |
E94280
|
entity |
| Predicate | regulationScope |
P5018
|
FINISHED |
| Object | recruiting |
—
|
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: recruiting | Statement: [NCAA Division I women’s track and field teams, regulationScope, recruiting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulationScope Context triple: [NCAA Division I women’s track and field teams, regulationScope, recruiting]
-
A.
subjectToRegulation
Indicates that an entity is governed, constrained, or controlled by a specific rule, law, or regulatory framework.
-
B.
regulationAtIssue
Indicates that a specific regulation is the subject of concern, dispute, or analysis in the given context.
-
C.
regulationImpact
Indicates how a regulation influences, constrains, or alters the behavior, performance, or outcomes associated with the related entities.
-
D.
scopeOfUse
chosen
Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
-
E.
regulatedIn
Indicates that one entity’s activity, expression, or occurrence is controlled, influenced, or modulated by another entity within a specific context 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.