Triple
T10523209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brigitte Bardot |
E248225
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Shalako |
E738631
|
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: Shalako | Statement: [Brigitte Bardot, notableWork, Shalako]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shalako Context triple: [Brigitte Bardot, notableWork, Shalako]
-
A.
Shalako
chosen
Shalako is a 1968 Western film starring Sean Connery and Brigitte Bardot, known for its blend of European aristocrats-in-peril and frontier action.
-
B.
The Trumpet Blows
The Trumpet Blows is a 1934 American drama film featuring Frances Drake alongside George Raft and Adolphe Menjou, set against the backdrop of the Mexican Revolution.
-
C.
Sula
Sula is a genus of large seabirds known as boobies, characterized by their strong diving ability and predominantly tropical oceanic distribution.
-
D.
Sula
Sula is a 1973 novel by American author Toni Morrison that explores Black female friendship, community, and identity in a small Ohio town.
-
E.
Sula
Sula is a coastal municipality in Møre og Romsdal county, Norway, known for its fishing industry, maritime heritage, and scenic island landscapes.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509e155b08190996325bf484ec55d |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90e1c73208190aa3d3e30aa4482ac |
completed | April 10, 2026, 2:50 p.m. |
Created at: April 6, 2026, 12:29 p.m.