Triple
T22410485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerry King |
E553981
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Pantera |
—
|
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: Pantera | Statement: [Kerry King, associatedAct, Pantera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pantera Context triple: [Kerry King, associatedAct, Pantera]
-
A.
Pantera
chosen
Pantera is a pioneering American heavy metal band known for shaping the groove metal subgenre with their aggressive sound and powerful riffs.
-
B.
Machine Head
Machine Head is an American heavy metal band from Oakland, California, known for its aggressive groove/thrash sound and influential albums like "Burn My Eyes."
-
C.
Machine Head
Machine Head is a 1972 hard rock album by Deep Purple, widely regarded as one of their definitive works and a classic of the genre.
-
D.
Megadeth
Megadeth is an American thrash metal band, founded by guitarist Dave Mustaine, known for its fast, technically complex music and influential role in shaping the genre.
-
E.
La Pantera
La Pantera is the nickname of Argentine professional footballer Gustavo Bou, a powerful forward known for his goal-scoring ability and physical style of play.
- 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15942edb081909869ae013ea72f09 |
completed | April 29, 2026, 1:05 a.m. |
Created at: April 16, 2026, 8:46 p.m.