Triple
T748524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA Division II Wrestling |
E15394
|
entity |
| Predicate | individualTitlesAwarded |
P2680
|
FINISHED |
| Object | national champion at each weight class |
—
|
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: national champion at each weight class | Statement: [NCAA Division II Wrestling, individualTitlesAwarded, national champion at each weight class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: individualTitlesAwarded Context triple: [NCAA Division II Wrestling, individualTitlesAwarded, national champion at each weight class]
-
A.
awardsTitle
chosen
Indicates that an entity confers or grants a specific title or honorific designation to another entity.
-
B.
mastersTitles
Indicates that one entity holds one or more master's degree titles associated with another entity (such as an institution, field, or program).
-
C.
numberOfAwards
Indicates the total count of awards that have been received by an entity.
-
D.
includesHonoraryAwardsFor
Indicates that one entity contains or lists honorary awards that have been granted to another entity.
-
E.
mostAwardsHolder
Indicates that the subject is the entity that holds the highest number of awards within a given group or 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62f31888190b80cb0a7220f8d80 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a5004f708190a984ee221716e19c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.