Triple
T3239367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fat Albert and the Cosby Kids |
E67930
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Bill |
E17085
|
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 | Statement: [Fat Albert and the Cosby Kids, character, Bill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Context triple: [Fat Albert and the Cosby Kids, character, Bill]
-
A.
Bill
Bill is a film featuring Mickey Rooney in a critically acclaimed dramatic role portraying a man with an intellectual disability.
-
B.
Bill
chosen
Bill is a common masculine given name, typically used as a diminutive or nickname for William.
-
C.
Billy
Billy is an English given name, commonly a diminutive of William, used for both real people and fictional characters.
-
D.
Billy
"Billy" is a song by English singer-songwriter James Blunt from his debut album *Back to Bedlam*.
-
E.
Ben
Ben is a common given name, typically used as a short form of names like Benedict or Benjamin.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef4c0bc819095e4f84296fe7cb6 |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2774f93448190b8493b457636ae48 |
completed | March 12, 2026, 8:20 a.m. |
Created at: March 8, 2026, 3:08 p.m.