Triple
T38222952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego State–Fresno State football rivalry |
E1012060
|
entity |
| Predicate | isIntradivisionalRivalry |
P10145
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [San Diego State–Fresno State football rivalry, isIntradivisionalRivalry, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isIntradivisionalRivalry Context triple: [San Diego State–Fresno State football rivalry, isIntradivisionalRivalry, true]
-
A.
isIntraStateRivalryOf
Indicates that there is a rivalry occurring within the same state or internal political unit between the related entities.
-
B.
isDivisionalMatchup
chosen
Indicates that the two entities (typically teams) are competing against each other within the same division.
-
C.
isMajorRivalryFor
Indicates that one entity is a primary or highly significant competitor or adversary to another, often characterized by ongoing, notable, or intense rivalry.
-
D.
hasRivalryIn
Indicates that two entities are in a state of competition or opposition within a specific domain, context, or field.
-
E.
hasRivalryContext
Indicates that there exists a competitive or adversarial relationship between entities within a specific situational or contextual framework.
- 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_69f76dd25e0c81909f2abd0803e5e3ee |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.