Triple
T15386421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiju War |
E367927
|
entity |
| Predicate | opponentForceName |
P99416
|
FINISHED |
| Object | kaiju |
—
|
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: kaiju | Statement: [Kaiju War, opponentForceName, kaiju]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opponentForceName Context triple: [Kaiju War, opponentForceName, kaiju]
-
A.
opponentForceCharacteristic
Indicates a characteristic or attribute that describes the nature, capability, or condition of an opposing force.
-
B.
opponentForceAllegiance
Indicates that one force, group, or individual is aligned with or belongs to an opposing or enemy side in a conflict or competition.
-
C.
enemyForceType
chosen
Indicates that one entity is characterized as a hostile or opposing force of a specified type relative to another entity.
-
D.
opponentFleet
Indicates that one fleet is in an adversarial or opposing relationship to another fleet.
-
E.
opposingForce
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e74ff70819094c1a85f51d6e228 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.