Triple
T355685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City FC |
E7536
|
entity |
| Predicate | hasIntenseRegionalRivalries |
P8277
|
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: [New York City FC, hasIntenseRegionalRivalries, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntenseRegionalRivalries Context triple: [New York City FC, hasIntenseRegionalRivalries, true]
-
A.
hasRivalryEmotion
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
-
B.
hasRivalryAspect
chosen
Indicates that there exists a competitive or adversarial relationship or dimension between entities.
-
C.
divisionRivalry
Indicates a competitive or adversarial relationship between entities that belong to the same division or subgroup within a larger organization or system.
-
D.
hasForeignRival
Indicates that an entity has at least one rival that is based in or originates from a different country or foreign jurisdiction.
-
E.
cityRivalry
Indicates a competitive or adversarial relationship that exists between two cities, often involving sports, economics, culture, or historical tensions.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebad8bf08190b4a38ffd9157d641 |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e9589e7c8190b2d3af8f858c96af |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.