Triple
T15386450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiju War |
E367927
|
entity |
| Predicate | outcomeInFirstFilm |
P83430
|
FINISHED |
| Object | Breach destroyed by human forces |
—
|
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: Breach destroyed by human forces | Statement: [Kaiju War, outcomeInFirstFilm, Breach destroyed by human forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: outcomeInFirstFilm Context triple: [Kaiju War, outcomeInFirstFilm, Breach destroyed by human forces]
-
A.
statusInFirstFilm
Indicates the role, condition, or situation an entity has in its first film appearance.
-
B.
statusAfterFirstFilm
Indicates the status or condition of an entity immediately following the release or completion of its first film.
-
C.
statusAtEndOfFilm
chosen
Indicates the condition or situation an entity is in when the film concludes.
-
D.
firstAppearanceFilm
Indicates the film in which an entity (such as a character or person) makes its first on-screen appearance.
-
E.
firstFilmTitle
Indicates the title of the first film associated with a given 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.