Triple
T38482725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alumni Field at Carol Hutchins Stadium |
E917825
|
entity |
| Predicate | primaryUseByGender |
P29732
|
FINISHED |
| Object | women |
—
|
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: women | Statement: [Alumni Field at Carol Hutchins Stadium, primaryUseByGender, women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryUseByGender Context triple: [Alumni Field at Carol Hutchins Stadium, primaryUseByGender, women]
-
A.
usedByGender
chosen
Indicates that something is utilized, applied, or engaged in by entities of a specified gender.
-
B.
primaryUseOf
Indicates that one entity serves as the main or principal function, purpose, or application of another entity.
-
C.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
D.
primaryHumanUse
Indicates the main way humans typically use, interact with, or benefit from the referenced entity.
-
E.
bearerGender
Indicates the gender associated with the bearer in the relationship or context.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.