Triple
T23366884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Daisley |
E593347
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Jake E. Lee |
—
|
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: Jake E. Lee | Statement: [Bob Daisley, workedWith, Jake E. Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake E. Lee Context triple: [Bob Daisley, workedWith, Jake E. Lee]
-
A.
Jake E. Lee
chosen
Jake E. Lee is an American hard rock and heavy metal guitarist best known for his work with Ozzy Osbourne in the 1980s and as the founder of the band Badlands.
-
B.
Jack Lee
Jack Lee was a British film director best known for his work on mid-20th-century dramas and war films.
-
C.
Jay Lee
Jay Lee is an actor best known for his role in the television miniseries adaptation of John Green's novel "Looking for Alaska."
-
D.
Eugene Lee
Eugene Lee was an acclaimed American theatrical set designer best known for his innovative, long-running work on Broadway productions and on "Saturday Night Live."
-
E.
Kenton Lee
Kenton Lee is a natural language processing researcher best known for leading the development of ELMo contextual word embeddings at Allen Institute for AI.
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0ad621881908a909f236e6e9c90 |
completed | April 29, 2026, 6:09 a.m. |
Created at: April 17, 2026, 5:32 p.m.