Triple
T1715420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WomenSportsFoundation |
E37277
|
entity |
| Predicate | nonprofitSector |
P9241
|
FINISHED |
| Object | sports and recreation |
—
|
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: sports and recreation | Statement: [WomenSportsFoundation, nonprofitSector, sports and recreation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonprofitSector Context triple: [WomenSportsFoundation, nonprofitSector, sports and recreation]
-
A.
nonProfitContext
Indicates that the relationship or action occurs within, is associated with, or is specifically relevant to a nonprofit or charitable organizational context.
-
B.
nonprofitType
Indicates the specific category or classification of a nonprofit organization based on its legal or functional type.
-
C.
fieldOfPhilanthropy
chosen
Indicates that an entity is engaged in or associated with a particular area or domain of philanthropic activity.
-
D.
isNonProfitProjectOf
Indicates that a project operates on a non-profit basis and is initiated, owned, or managed by the referenced entity.
-
E.
nonprofitStatus
Indicates that an entity operates as a nonprofit organization, typically meeting legal or regulatory criteria for nonprofit status.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab7521878c8190b9e7739b8c3fc705 |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61bd46d48190915500d75a9d8e94 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.