Triple
T14946787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Virginia Intercollegiate Athletic Conference |
E372681
|
entity |
| Predicate | hadMenSports |
P7453
|
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: [West Virginia Intercollegiate Athletic Conference, hadMenSports, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMenSports Context triple: [West Virginia Intercollegiate Athletic Conference, hadMenSports, yes]
-
A.
hasMenTeam
Indicates that an entity possesses, is associated with, or fields a men’s team.
-
B.
hasSportsBody
Indicates that an entity possesses a body or physique that is characteristic of someone who regularly engages in sports or athletic activities.
-
C.
hasSportsStatus
Indicates that an entity holds a particular sports-related status, role, or classification (such as amateur, professional, active, or retired) within a sporting context.
-
D.
sportGender
chosen
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
E.
hasAthlete
Indicates a relationship where an entity (such as a team, organization, or event) includes or is associated with one or more athletes.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68e35c481908e47cd68441c5115 |
completed | April 15, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:39 a.m.