Triple
T4946746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red River Showdown |
E111068
|
entity |
| Predicate | rivalryEmotion |
P5079
|
FINISHED |
| Object | highly passionate fan bases |
—
|
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: highly passionate fan bases | Statement: [Red River Showdown, rivalryEmotion, highly passionate fan bases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rivalryEmotion Context triple: [Red River Showdown, rivalryEmotion, highly passionate fan bases]
-
A.
rivalryLevel
Indicates the degree or intensity of competitive opposition or conflict between two entities.
-
B.
hasRivalryEmotion
chosen
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
-
C.
typeOfRivalry
Indicates a competitive or adversarial relationship between entities, specifying the particular kind or nature of rivalry that exists between them.
-
D.
rivalryStatus
Indicates a competitive or adversarial relationship between entities, often involving ongoing opposition or contention.
-
E.
rivalryBasis
Indicates the underlying reason, cause, or grounds on which a rivalry between entities is based.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70abf8dc819090269d0e1ce9f871 |
completed | March 20, 2026, 4:07 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.