Triple
T24529469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of McFarland |
E606761
|
entity |
| Predicate | representedInFilm |
P93382
|
FINISHED |
| Object | McFarland, USA |
—
|
NE NERFINISHED |
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: McFarland, USA | Statement: [City of McFarland, representedInFilm, McFarland, USA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representedInFilm Context triple: [City of McFarland, representedInFilm, McFarland, USA]
-
A.
mentionedInFilm
Indicates that an entity is referenced or talked about within the content of a film.
-
B.
includedInFilm
Indicates that one entity (such as a scene, segment, or element) is contained within or forms part of a particular film.
-
C.
visitedInFilm
chosen
Indicates that a location or place is depicted as being visited by a character within the events of a film.
-
D.
laterDepictedIn
Indicates that an entity is portrayed or represented in a depiction (such as an image, artwork, or illustration) that was created at a later time than the entity itself.
-
E.
basedInFilm
Indicates that something (such as a character, event, or work) is situated, set, or primarily located within the context or universe of a particular film.
- 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_69e2c4c90c848190b23c4303620dcaaf |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:25 a.m.