Triple
T6061826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 南次郎 |
E135048
|
entity |
| Predicate | 歴史的文脈 |
P1409
|
FINISHED |
| Object | 日中戦争期 |
—
|
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: 日中戦争期 | Statement: [南次郎, 歴史的文脈, 日中戦争期]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 歴史的文脈 Context triple: [南次郎, 歴史的文脈, 日中戦争期]
-
A.
hasHistoricalContext
chosen
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
-
B.
historical
Indicates that the subject has existed, occurred, or been relevant in the past rather than in the present or future.
-
C.
shareHistoricalContextAs
Indicates that two or more entities are associated with or understood within the same historical background, period, or circumstances.
-
D.
historicalBackground
Indicates that one entity provides contextual historical information or circumstances that help explain the origin, development, or significance of another entity.
-
E.
historicallyEncompassed
Indicates that one entity previously included, covered, or contained another entity within its scope, extent, or boundaries during a past historical period.
- 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_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0572100e8819084c3174921a2d527 |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049f031408190b08b2766237c5dd0 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:10 p.m.