Triple
T27958751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Mi |
E704521
|
entity |
| Predicate | hasRivalState |
P172365
|
FINISHED |
| Object | State of Jin |
—
|
NE NERFINISHED |
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: State of Jin | Statement: [House of Mi, hasRivalState, State of Jin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRivalState Context triple: [House of Mi, hasRivalState, State of Jin]
-
A.
hasInStateRivalries
Indicates that two entities are rivals or competitors within the same state or internal jurisdiction.
-
B.
hasForeignRival
Indicates that an entity has at least one rival that is based in or originates from a different country or foreign jurisdiction.
-
C.
hasLocalRivalry
Indicates that there is an ongoing competitive or adversarial relationship between entities that are geographically close or share the same local area.
-
D.
hasRivalrySport
Indicates a competitive relationship in which two entities are rivals specifically within the context of a sport or sporting activity.
-
E.
hasRivalryContext
Indicates that there exists a competitive or adversarial relationship between entities within a specific situational or contextual framework.
- F. None of above. chosen
Provenance (4 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_69ef841061e48190b5570f9562f7434d |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6abe15d5c81909ccf4ce37f78bc43 |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1c555081908787dbf76147f180 |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aaf31a548190b2f792ff4b8c002a |
completed | May 3, 2026, 1:54 a.m. |
Created at: April 27, 2026, 7:30 p.m.