Triple
T34926271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rockwell Torrey |
E1007294
|
entity |
| Predicate | hasRankAtStartOfFilm |
P187587
|
FINISHED |
| Object | Captain |
—
|
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: Captain | Statement: [Rockwell Torrey, hasRankAtStartOfFilm, Captain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankAtStartOfFilm Context triple: [Rockwell Torrey, hasRankAtStartOfFilm, Captain]
-
A.
hasRankAtTimeOfFilm
chosen
Indicates that an entity held a specific rank or position during the time period in which a particular film is set or produced.
-
B.
statusAtStartOfFilm
Indicates the condition or situation an entity is in at the beginning of the film.
-
C.
legalStatusAtStartOfFilm
Indicates the legal condition or standing an entity has at the beginning of the film’s narrative.
-
D.
worksForAtStartOfFilm
Indicates that one entity is employed by or working for another entity at the beginning of the film's narrative.
-
E.
beginsWithFilm
Indicates that one entity (typically a series, collection, or sequence) starts or is initiated with a particular film as its first element.
- 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_69f76dc3d83881909d5c3c14455cfa2c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: May 3, 2026, 4 p.m.