Triple
T6085554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim France |
E135630
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jim France |
E135630
|
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: Jim France | Statement: [Jim France, name, Jim France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jim France Context triple: [Jim France, name, Jim France]
-
A.
Jim France
chosen
Jim France is an American motorsports executive and member of the France family who serves as the current leader of NASCAR.
-
B.
Patrick Lussier
Patrick Lussier is a Canadian film editor, director, and frequent Wes Craven collaborator known for his work in the horror genre.
-
C.
Peter Dombrowski
Peter Dombrowski is a scholar known for his work in international relations and maritime security studies.
-
D.
John Laroche
John Laroche is a real-life eccentric plant dealer and orchid poacher whose obsessive personality and legal troubles inspired a central character in the film and book "Adaptation."
-
E.
Roger Taillibert
Roger Taillibert was a French architect renowned for his innovative, sculptural modernist designs, most famously the Olympic Stadium in Montreal.
- 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057891dc88190997c4e32b2261fb3 |
completed | March 22, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d60e824819098a9f5fc5cc00be4 |
completed | March 23, 2026, 11 a.m. |
Created at: March 22, 2026, 4:12 p.m.