Triple
T21389466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Dworkin |
E527601
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Matador |
—
|
NE NERFINISHED |
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: Matador | Statement: [Dan Dworkin, notableWork, Matador]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matador Context triple: [Dan Dworkin, notableWork, Matador]
-
A.
Matador
"Matador" is a song by the American rock band Spirit, known for blending psychedelic rock with jazz and progressive influences.
-
B.
Matador
Matador is a 1986 Spanish psychological thriller film directed by Pedro Almodóvar that explores themes of desire, death, and obsession.
-
C.
Matador
Matador is a tire brand associated with Continental AG, offering a range of affordable passenger and commercial vehicle tires primarily in European and global markets.
-
D.
Matador
Matador is a small rural town in the Texas Panhandle that serves as the administrative and commercial hub of Motley County.
-
E.
Matador
chosen
Matador is a 2014 American action-comedy television series that follows a charismatic soccer star who secretly works as a CIA operative.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0f8ae288190b43df9fe2841a822 |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:13 p.m.