Triple
T4638019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese battlecruiser Amagi |
E101580
|
entity |
| Predicate | designedOpponents |
P47072
|
FINISHED |
| Object | United States Navy capital ships |
—
|
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: United States Navy capital ships | Statement: [Japanese battlecruiser Amagi, designedOpponents, United States Navy capital ships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedOpponents Context triple: [Japanese battlecruiser Amagi, designedOpponents, United States Navy capital ships]
-
A.
consideredOpponentsAs
Indicates that one entity regarded or treated another entity as an opponent or adversary.
-
B.
designedToDefeat
chosen
Indicates that one entity is intentionally created or configured with the purpose of overcoming, neutralizing, or rendering ineffective another entity.
-
C.
opponentInCase
Indicates that two parties are on opposing sides in the same legal case or proceeding.
-
D.
battleOpponent
Indicates that two entities are engaged in or designated as opponents in a battle or combat scenario.
-
E.
opponentStrategy
Indicates that one entity employs or represents a strategic plan specifically designed to counter or compete against another entity.
- 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a64214481908a207e8070cc7a45 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.