Triple
T1088365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oregon State Beavers women’s golf |
E24103
|
entity |
| Predicate | competitionGenderCategory |
P7453
|
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: [Oregon State Beavers women’s golf, competitionGenderCategory, women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: competitionGenderCategory Context triple: [Oregon State Beavers women’s golf, competitionGenderCategory, women]
-
A.
competitionClass
Indicates that one entity is classified into a particular competitive category or level within a competition or contest.
-
B.
sportGender
chosen
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
C.
competitionOf
Indicates a relationship where one entity is the competitive event, contest, or rivalry involving another entity.
-
D.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
-
E.
typeOfCompetition
Indicates the specific kind or category of competition in which an entity participates or is involved.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b97d85708190a1630256648aa4a2 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b741b0cc8190be001a16a81f6d9e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.