Triple
T5283375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Blackbird (1926 film) |
E119551
|
entity |
| Predicate | hasFilmType |
P9709
|
FINISHED |
| Object | narrative feature |
—
|
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: narrative feature | Statement: [The Blackbird (1926 film), hasFilmType, narrative feature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmType Context triple: [The Blackbird (1926 film), hasFilmType, narrative feature]
-
A.
producedFilmType
Indicates that an entity (such as a person or organization) was responsible for producing a film of a specified type or category.
-
B.
hasFilmStyle
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
-
C.
filmType
chosen
Indicates the specific category or genre that a film belongs to.
-
D.
distributedFilmType
Indicates that a film was distributed in a particular format or category of distribution.
-
E.
hasNotableFilm
Indicates that an entity is associated with a film that is considered significant, well-known, or particularly noteworthy.
- 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_69bd446d05a8819092ad333a3f9c8d5c |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8c9c72b08190947b6b955ac1bb5a |
completed | March 20, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69bd844a56b48190ad743c42246e02dd |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:52 p.m.