Triple
T35469875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheelsy, South Carolina |
E1025177
|
entity |
| Predicate | associatedWithYearOfFilmRelease |
P56244
|
FINISHED |
| Object | 2006 |
—
|
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: 2006 | Statement: [Wheelsy, South Carolina, associatedWithYearOfFilmRelease, 2006]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithYearOfFilmRelease Context triple: [Wheelsy, South Carolina, associatedWithYearOfFilmRelease, 2006]
-
A.
associatedWithYearFilm
chosen
Indicates a relationship where something (such as an event, award, or record) is linked to or pertains to a specific film released or identified in a given year.
-
B.
associatedWithReleaseDateOfFilm
Indicates a relationship where something is connected to or corresponds with the release date of a film.
-
C.
associatedWithLeadActorOfFilm
Indicates a relationship where one entity is connected or linked in some relevant way to the lead actor of a specified film.
-
D.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
E.
associatedWithProducerOfFilm
Indicates that one entity has an association or connection with the producer 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_69f76dfa20d0819089585dc2cf653aea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:04 p.m.