Triple
T6337615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 重光 葵 |
E142529
|
entity |
| Predicate | 関連する国際関係 |
P15536
|
FINISHED |
| Object | 連合国との講和交渉 |
—
|
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: 連合国との講和交渉 | Statement: [重光 葵, 関連する国際関係, 連合国との講和交渉]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連する国際関係 Context triple: [重光 葵, 関連する国際関係, 連合国との講和交渉]
-
A.
関係する国際的出来事
Indicates a relationship where something is connected to, involved in, or affected by an international event.
-
B.
internationalInstitutionRelationship
Indicates a relationship in which one entity is connected to, interacts with, or is associated with an international institution (such as through membership, partnership, oversight, or collaboration).
-
C.
politicalRelation
Indicates a relationship between entities that involves political alignment, influence, affiliation, conflict, or cooperation within a political context.
-
D.
internationalAffairsFunction
Indicates a functional role or responsibility related to managing, coordinating, or influencing interactions and relationships between entities across national borders.
-
E.
diplomaticRelation
chosen
Indicates a formal relationship of negotiation, communication, or representation between political entities, typically states or governments.
- 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_69c008d4d8e88190ad301c05b08722ac |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0654e11988190b708426d3003716a |
completed | March 22, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69c060e7e2d48190af9d004236466788 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:30 p.m.