Triple
T38222940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego State–Fresno State football rivalry |
E1012060
|
entity |
| Predicate | trophyIntroducedInDecade |
P190322
|
FINISHED |
| Object | 2010s |
—
|
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: 2010s | Statement: [San Diego State–Fresno State football rivalry, trophyIntroducedInDecade, 2010s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trophyIntroducedInDecade Context triple: [San Diego State–Fresno State football rivalry, trophyIntroducedInDecade, 2010s]
-
A.
trophyIntroducedInSeason
Indicates the season in which a particular trophy was first introduced or became part of a competition or series.
-
B.
trophyNameRefersTo
Indicates that a given trophy name refers to, denotes, or is associated with a particular trophy entity.
-
C.
trophyOrigin
Indicates the source or place from which a trophy was obtained or originated.
-
D.
trophyCount
Indicates the number of trophies associated with a given entity.
-
E.
trophyOfficialName
Indicates the official, formally recognized name assigned to a particular trophy.
- F. None of above. chosen
Provenance (4 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_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc42b9334819099929649b7ef68ea |
completed | May 7, 2026, 4:56 p.m. |
Created at: May 3, 2026, 4:30 p.m.