Triple
T1441334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Connecticut Huskies athletics |
E31077
|
entity |
| Predicate | genderEquity |
P25470
|
FINISHED |
| Object | fields men's and women's varsity teams |
—
|
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: fields men's and women's varsity teams | Statement: [University of Connecticut Huskies athletics, genderEquity, fields men's and women's varsity teams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderEquity Context triple: [University of Connecticut Huskies athletics, genderEquity, fields men's and women's varsity teams]
-
A.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
-
B.
genderDivision
chosen
Indicates a relationship where roles, responsibilities, or categories are separated or distinguished based on gender.
-
C.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
D.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
-
E.
formerGenderAdmission
Indicates that an institution previously admitted a particular gender but no longer does so.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c478f65481909ee716791c663491 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.