Triple
T10248330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy Dawson |
E240276
|
entity |
| Predicate | roleInTheGrandBudapestHotel |
P93184
|
FINISHED |
| Object | producer |
—
|
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: producer | Statement: [Jeremy Dawson, roleInTheGrandBudapestHotel, producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTheGrandBudapestHotel Context triple: [Jeremy Dawson, roleInTheGrandBudapestHotel, producer]
-
A.
roleInSyriana
Indicates that one entity has a specific role or involvement in the context of "Syriana," such as participation, function, or contribution related to it.
-
B.
theaterRole
Indicates that an entity holds or performs a specific role or character in a theatrical production in relation to another entity (such as a play or performance).
-
C.
roleInScene
Indicates that an entity participates in a particular scene with a specific role or function within that scene.
-
D.
speakerRole
Indicates the functional role or capacity in which an entity is acting as a speaker within a communicative event.
-
E.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d328272c8190a3548d7f7f38cfc4 |
completed | April 7, 2026, 9:49 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ebd6c88190a1f3f4a72a99d6fe |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d32741888190928b045e2241cfac |
completed | April 7, 2026, 9:49 a.m. |
Created at: April 6, 2026, 11:27 a.m.