Triple
T32489544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokohama derby |
E830341
|
entity |
| Predicate | regionRivalryType |
P29010
|
FINISHED |
| Object | intra-city rivalry |
—
|
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: intra-city rivalry | Statement: [Yokohama derby, regionRivalryType, intra-city rivalry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionRivalryType Context triple: [Yokohama derby, regionRivalryType, intra-city rivalry]
-
A.
rivalryRegion
Indicates a competitive or adversarial relationship that exists between entities within a specific geographic or regional context.
-
B.
typeOfRivalry
chosen
Indicates a competitive or adversarial relationship between entities, specifying the particular kind or nature of rivalry that exists between them.
-
C.
rivalryBasis
Indicates the underlying reason, cause, or grounds on which a rivalry between entities is based.
-
D.
countryRivalryContext
Indicates a relationship where two countries are in a state of rivalry, competition, or conflict within a specific political, historical, or strategic context.
-
E.
associatedRivalry
Indicates a relationship where one entity is linked to another as its rival, competitor, or opposing counterpart.
- 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_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fee25dbca481909e6f1c255122b3a8 |
completed | May 9, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69fee1c8915c8190b08b63e42881f1a9 |
completed | May 9, 2026, 7:27 a.m. |
Created at: May 1, 2026, 12:59 a.m.