Triple
T4449271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seattle Thunderbirds |
E96366
|
entity |
| Predicate | hasRegionalRivalries |
P18267
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Seattle Thunderbirds, hasRegionalRivalries, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalRivalries Context triple: [Seattle Thunderbirds, hasRegionalRivalries, yes]
-
A.
hasLocalRivalry
chosen
Indicates that there is an ongoing competitive or adversarial relationship between entities that are geographically close or share the same local area.
-
B.
hasRivalryAspect
Indicates that there exists a competitive or adversarial relationship or dimension between entities.
-
C.
hasHistoricRivalry
Indicates a long-standing, often competitive or adversarial relationship between two entities, typically rooted in significant past conflicts or repeated opposition.
-
D.
hasRivalryEmotion
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
-
E.
hasForeignRival
Indicates that an entity has at least one rival that is based in or originates from a different country or foreign jurisdiction.
- 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355d5975c8190bfe8a2d5d2dbf075 |
completed | March 13, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69b34f62c180819097ced38da2052207 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:32 p.m.