Triple
T10609109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Eagles |
E275957
|
entity |
| Predicate | otherSports |
P90075
|
FINISHED |
| Object | women's basketball |
—
|
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's basketball | Statement: [Golden Eagles, otherSports, women's basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherSports Context triple: [Golden Eagles, otherSports, women's basketball]
-
A.
otherSportsCovered
chosen
Indicates that additional sports, beyond a primary or main sport, are also included or reported on.
-
B.
sportsAndRecreation
Indicates a relationship where an entity is associated with, involved in, or designated for sports or recreational activities.
-
C.
otherSportIndustry
Indicates a relationship where an entity is involved in, associated with, or belongs to a sports-related industry other than the primary or specified one.
-
D.
sport
Indicates that an entity participates in, is associated with, or is characterized by a particular athletic activity or game.
-
E.
traditionalSport
Indicates that an entity is a sport practiced within a culture or community that has been passed down over generations and is recognized as part of traditional or heritage activities.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df4d0a6881909fea20378085173d |
completed | April 8, 2026, 11:05 p.m. |
| PD | Predicate disambiguation | batch_69d6dd72c1288190adbb5e79e94c044a |
completed | April 8, 2026, 10:57 p.m. |
Created at: April 8, 2026, 7:32 p.m.