Triple
T6844454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Attu |
E157856
|
entity |
| Predicate | U.S.ForcesStrength |
P11878
|
FINISHED |
| Object | approximately 15,000 troops |
—
|
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: approximately 15,000 troops | Statement: [Battle of Attu, U.S.ForcesStrength, approximately 15,000 troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: U.S.ForcesStrength Context triple: [Battle of Attu, U.S.ForcesStrength, approximately 15,000 troops]
-
A.
USForces
Indicates the presence, involvement, or deployment of United States military forces in relation to a specified location, event, or entity.
-
B.
primaryUSForces
Indicates that the referenced forces constitute the main or principal contingent of United States military forces in a given context or operation.
-
C.
USForceType
Indicates the type or category of U.S. military force involved in a given relationship or action.
-
D.
warTimeStrengthApprox
chosen
Indicates an approximate measure of an entity’s military strength or capacity during a time of war.
-
E.
strengthGovernmentForces
Indicates the level or degree of military or coercive power held or exerted by government forces in a given 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_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. |
Created at: March 27, 2026, 2:19 p.m.