Triple
T4898869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA women’s golf |
E109747
|
entity |
| Predicate | teamSizeTypical |
P3668
|
FINISHED |
| Object | 5 players in competition lineup |
—
|
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: 5 players in competition lineup | Statement: [NCAA women’s golf, teamSizeTypical, 5 players in competition lineup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamSizeTypical Context triple: [NCAA women’s golf, teamSizeTypical, 5 players in competition lineup]
-
A.
typicalTeamSize
chosen
Indicates the usual or most common number of members that make up a given team.
-
B.
typicalGroupSizeRange
Indicates the usual minimum and maximum number of individuals that typically occur together in a group for the given entity.
-
C.
staffSize
Indicates the number of staff members associated with an entity.
-
D.
collaborationSize
Indicates the number of participants involved together in a given collaborative relationship or activity.
-
E.
teamCountType
Indicates how the number of teams is categorized or measured within a given context.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:28 p.m.