Triple
T6844449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Attu |
E157856
|
entity |
| Predicate | JapaneseTactics |
P73471
|
FINISHED |
| Object | banzai charge |
—
|
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: banzai charge | Statement: [Battle of Attu, JapaneseTactics, banzai charge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JapaneseTactics Context triple: [Battle of Attu, JapaneseTactics, banzai charge]
-
A.
JapaneseForceStrength
Indicates the size or magnitude of the Japanese military forces involved in a particular context or operation.
-
B.
JapaneseFormation
Indicates a relationship where something is formed, created, or organized according to Japanese style, methods, or origin.
-
C.
JapaneseAdvantage
Indicates that one party holds a comparative advantage or superior position specifically in a Japanese context (e.g., language, market, culture, or environment) relative to another.
-
D.
japaneseVariant
Indicates that one entity is a Japanese-language or Japan-specific variant or version of another entity.
-
E.
PersianTactics
Indicates the use or application of military strategies, maneuvers, or methods characteristic of Persian forces in a conflict or battle context.
- 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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6b8627081908e34d2b942d08aef |
completed | March 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69c6d09f90648190bc0a462c7d59de1b |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d623aba88190a93ec9c83508c960 |
completed | March 27, 2026, 7:10 p.m. |
Created at: March 27, 2026, 2:19 p.m.