Triple
T22891974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skin Yard |
E568063
|
entity |
| Predicate | hasFormerMember |
P1168
|
FINISHED |
| Object | Burke Thomas |
—
|
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: Burke Thomas | Statement: [Skin Yard, hasFormerMember, Burke Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burke Thomas Context triple: [Skin Yard, hasFormerMember, Burke Thomas]
-
A.
Burke Thomas
chosen
Burke Thomas is an American drummer best known for his work with the Seattle grunge band Skin Yard.
-
B.
Burke Baker
Burke Baker was a benefactor whose contributions to science education led to a prominent planetarium in Houston being named in his honor.
-
C.
Burke Moses
Burke Moses is an American actor and singer best known for originating the role of Gaston in the Broadway production of Disney’s "Beauty and the Beast."
-
D.
Matthew Burril
Matthew Burril is a Republican politician who ran for his party’s nomination in North Carolina’s 11th congressional district during the 2022 U.S. House elections.
-
E.
Burke Hayes
Burke Hayes was one of the founding figures behind CH2M Hill, a major American engineering and construction firm.
- 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f17fc66dbc81909b31c068d7f2c531 |
completed | April 29, 2026, 3:49 a.m. |
Created at: April 17, 2026, 3:40 p.m.