Triple
T8441419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Statham |
E199358
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Parker |
E545941
|
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: Parker | Statement: [Jason Statham, notableWork, Parker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parker Context triple: [Jason Statham, notableWork, Parker]
-
A.
Parker
Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
-
B.
Parker
chosen
Parker is a 2013 American crime thriller film starring Jason Statham as a professional thief who seeks revenge after being double-crossed by his crew.
-
C.
Tucker
Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
-
D.
Spencer
Spencer is a small town in central Massachusetts known for its New England character and historic mill village roots.
-
E.
Spencer
Spencer is a 2021 biographical psychological drama film depicting Princess Diana during a tense Christmas holiday with the British royal family, starring Kristen Stewart in the lead role.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe138a94081908e306d22aaa39b24 |
completed | March 31, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d9ab3a88190ada7741cf054fc1b |
completed | April 2, 2026, 7:41 a.m. |
Created at: March 30, 2026, 6:08 p.m.