Triple
T4416127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 大田実 |
E94977
|
entity |
| Predicate | 関連主題 |
P55522
|
FINISHED |
| Object | 沖縄戦における民間人被害 |
—
|
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: 沖縄戦における民間人被害 | Statement: [大田実, 関連主題, 沖縄戦における民間人被害]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連主題 Context triple: [大田実, 関連主題, 沖縄戦における民間人被害]
-
A.
majorThemeAssociation
Indicates that one entity is associated with another as a primary or central theme.
-
B.
subtheme
Indicates that one topic or concept functions as a more specific, subordinate theme within a broader overarching theme.
-
C.
centralThemeConnection
Indicates a relationship where one element serves as the primary or unifying theme that conceptually links or organizes the other element(s).
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
featuresTopic
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
- 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551afb448190a2ce2000193808ac |
completed | March 13, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff7018c81908ad8597e525c042b |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:29 p.m.