Triple
T25399929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 大阪城 |
E636391
|
entity |
| Predicate | 関係する戦い |
P117285
|
FINISHED |
| Object | 大坂冬の陣 |
—
|
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: 大坂冬の陣 | Statement: [大阪城, 関係する戦い, 大坂冬の陣]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関係する戦い Context triple: [大阪城, 関係する戦い, 大坂冬の陣]
-
A.
関連戦争
Indicates a relationship where an entity is associated with, connected to, or involved in a particular war or military conflict.
-
B.
battleRelatedTo
chosen
Indicates a relationship where one entity is connected to, associated with, or relevant to a particular battle or combat event.
-
C.
associatedWithBattle
Indicates a relationship where an entity is connected or linked to a specific battle, such as by participation, relevance, or involvement.
-
D.
関与作戦
Indicates a relationship where an entity is involved in, participates in, or contributes to the execution of a specific operation or mission.
-
E.
associatedWithWar
Indicates a relationship where an entity is connected or related to war, such as by involvement, influence, cause, or context.
- 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f584f978a881909842e36f61b9a40a |
completed | May 2, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 1:50 p.m.