Triple
T5751332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J-Squad |
E126858
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Kimmel |
E387376
|
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: Kimmel | Statement: [J-Squad, member, Kimmel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kimmel Context triple: [J-Squad, member, Kimmel]
-
A.
Jimmy Kimmel
chosen
Jimmy Kimmel is an American television host, comedian, writer, and producer best known for hosting the late-night talk show "Jimmy Kimmel Live!" on ABC.
-
B.
Ellen DeGeneres
Ellen DeGeneres is an American comedian, actress, and television host best known for her groundbreaking sitcom "Ellen" and her long-running daytime talk show "The Ellen DeGeneres Show."
-
C.
Elliott DeGeneres
Elliott DeGeneres is a member of the DeGeneres family, related to American actor, comedian, and musician Vance DeGeneres.
-
D.
Jon Tenney
Jon Tenney is an American actor best known for his role as FBI Special Agent Fritz Howard on the television crime drama series "The Closer."
-
E.
Mark Leno
Mark Leno is an American Democratic politician and former California state legislator known for representing San Francisco in both the State Assembly and State Senate.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0288a0ea8819091ac6f965471ceee |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e3a50b88190a943b2d91d3c5b8e |
completed | March 22, 2026, 11:41 p.m. |
Created at: March 22, 2026, 3:48 p.m.