Triple
T20157448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clem Burke |
E491610
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Clem Burke |
—
|
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: Clem Burke | Statement: [Clem Burke, name, Clem Burke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clem Burke Context triple: [Clem Burke, name, Clem Burke]
-
A.
Clem Burke
chosen
Clem Burke is an American drummer best known for his long-time work with the rock band Blondie.
-
B.
Joseph Clemons
Joseph Clemons is a person most likely known in this context as the primary user or bearer of the name "Clemons."
-
C.
Jack Bicknell
Jack Bicknell is an American football coach best known for leading Boston College to national prominence in the 1980s, including the famed Doug Flutie era and the 1984 Cotton Bowl victory.
-
D.
Leon Barmore
Leon Barmore is a legendary women's college basketball coach best known for leading the Louisiana Tech Lady Techsters to national prominence and multiple NCAA championships.
-
E.
Big John Harrigan
Big John Harrigan is a character from the film "L.I.E." who serves as a complex, morally ambiguous figure influencing the troubled teenage protagonist.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e18a0c8190a2cc2b305da28047 |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:34 p.m.