Triple
T10776358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midnight in Paris |
E254207
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Gravier Productions |
E574180
|
NE 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: Gravier Productions | Statement: [Midnight in Paris, productionCompany, Gravier Productions]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gravier Productions Context triple: [Midnight in Paris, productionCompany, Gravier Productions]
-
A.
Gravier Productions
chosen
Gravier Productions is an American film production company best known for producing many of Woody Allen’s later films, including "Blue Jasmine."
-
B.
Grive Productions
Grive Productions is a film production company best known for its involvement in the action-thriller movie "Taken."
-
C.
Dijon Productions
Dijon Productions was a mid-20th-century American film production company best known for producing the 1958 crime drama "Thunder Road."
-
D.
Brut Productions
Brut Productions was a film production company active in the 1970s, known for backing a range of offbeat and genre films.
-
E.
Le Grisbi Productions
Le Grisbi Productions is a French film production company known for backing a range of international and auteur-driven cinema projects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7329d8c908190bddad40685133ea1 |
completed | April 9, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de238ff88881908676d38dca041cb4 |
completed | April 14, 2026, 11:22 a.m. |
Created at: April 8, 2026, 9:16 p.m.