Triple
T2020569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas–New York |
E44094
|
entity |
| Predicate | sportsRivalryBetween |
P22658
|
FINISHED |
| Object | Dallas-based teams |
—
|
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: Dallas-based teams | Statement: [Texas–New York, sportsRivalryBetween, Dallas-based teams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsRivalryBetween Context triple: [Texas–New York, sportsRivalryBetween, Dallas-based teams]
-
A.
divisionRivalry
Indicates a competitive or adversarial relationship between entities that belong to the same division or subgroup within a larger organization or system.
-
B.
rivalOf
chosen
Indicates a relationship in which two entities compete against or oppose each other, often seeking advantage in the same domain or objective.
-
C.
hasRivalryEmotion
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
-
D.
hasRivalryAspect
Indicates that there exists a competitive or adversarial relationship or dimension between entities.
-
E.
notableRivalry
Indicates a significant, well-recognized competitive or adversarial relationship between two entities.
- 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8d0bcbc8190bbbb726ecae1c51b |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb7a389408190a84a54856352f15b |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:38 p.m.