Triple
T20996882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wild Strawberries |
E517171
|
entity |
| Predicate | hasFilmForm |
P142412
|
FINISHED |
| Object | feature film |
—
|
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: feature film | Statement: [Wild Strawberries, hasFilmForm, feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmForm Context triple: [Wild Strawberries, hasFilmForm, feature film]
-
A.
hasFilmStructure
Indicates that one entity possesses or is organized according to the narrative or formal structure of a film.
-
B.
hasTheatricalForm
Indicates that something is associated with or presented in a particular theatrical form or style.
-
C.
hasLiveActionFilm
Indicates that a subject has a corresponding live-action film adaptation or representation.
-
D.
hasTheatricalFilm
Indicates that an entity has an associated theatrical film adaptation, version, or release.
-
E.
hasFirstFilm
Indicates the specific film that is recognized as the first film associated with an entity (such as a person, series, or franchise).
- F. None of above. chosen
Provenance (4 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc21838081909872eed21bc12a08 |
completed | April 21, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e5dbec80708190a49bccab7ff97e7b |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2df1a888190b5b478e76bdf7fdf |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 1:51 p.m.