Triple
T5588768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cobbs |
E146823
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Bill Cobbs |
E27362
|
NE FINISHED |
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: Bill Cobbs | Statement: [Cobbs, usedBy, Bill Cobbs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Cobbs Context triple: [Cobbs, usedBy, Bill Cobbs]
-
A.
Bill Cobbs
chosen
Bill Cobbs is an American character actor known for his prolific supporting roles in film and television, including appearances in movies like "Night at the Museum," "Demolition Man," and "The Hudsucker Proxy."
-
B.
Roger Cobb
Roger Cobb is the harried, skeptical lawyer who becomes comically entangled with a deceased heiress’s spirit in the 1984 fantasy-comedy film "All of Me."
-
C.
Allen Gamble
Allen Gamble is a mild-mannered, desk-bound NYPD detective portrayed by Will Ferrell in the action-comedy film "The Other Guys."
-
D.
Don Bailey
Don Bailey is an architect best known for designing the Perth Concert Hall in Western Australia.
-
E.
Hank Booth
Hank Booth is a recurring character on the television series "Bones," known as Seeley Booth's grandfather and a former Army veteran.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0209e892c8190b936a05ef2a14d36 |
completed | March 22, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d2f8710819094f5d052b767b9a6 |
completed | March 22, 2026, 8:12 p.m. |
Created at: March 22, 2026, 3:38 p.m.