Triple
T33113442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nick Vallelonga |
E847390
|
entity |
| Predicate | producedAwardWinningFilm |
P93687
|
FINISHED |
| Object | Green Book |
—
|
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: Green Book | Statement: [Nick Vallelonga, producedAwardWinningFilm, Green Book]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: producedAwardWinningFilm Context triple: [Nick Vallelonga, producedAwardWinningFilm, Green Book]
-
A.
producedFilm
Indicates that one entity served as the producer (or production company) responsible for making or financing the creation of a particular film.
-
B.
associatedAwardWinningFilm
chosen
Indicates that there is a relationship between an entity and a film with which it is connected, where that film has received an award.
-
C.
filmWon
Indicates that a film has received or been awarded a particular prize, honor, or recognition.
-
D.
firstAwardedForFilm
Indicates the film for which an entity (such as a person or award) was first given or received an award.
-
E.
producedFilmType
Indicates that an entity (such as a person or organization) was responsible for producing a film of a specified type or category.
- 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_69f3495751a081909850af5843da40dc |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe189fec148190aeef51b417ba15b0 |
completed | May 8, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69fe17285b0881908de7569d8dbd20bd |
completed | May 8, 2026, 5:02 p.m. |
Created at: May 1, 2026, 1:27 a.m.