Triple
T22192068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of DuPage athletic teams |
E548450
|
entity |
| Predicate | offersWomen'sSports |
P80775
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [College of DuPage athletic teams, offersWomen'sSports, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersWomen'sSports Context triple: [College of DuPage athletic teams, offersWomen'sSports, yes]
-
A.
sportGender
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
B.
hasFemaleCompetitors
Indicates that an entity participates in a competitive context where at least some of the competitors are female.
-
C.
eventsForWomen
Indicates that the associated events are intended for, targeted at, or specifically involve women.
-
D.
numberOfFemaleAthletes
Indicates the count of athletes who are female in a given context or group.
-
E.
includesWomen'sLeagues
chosen
Indicates that the subject entity encompasses, offers, or is associated with one or more leagues specifically organized for women.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12ae49ec881908fa42446b19e3f2d |
completed | April 28, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:35 p.m.