Triple
T562466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jay Leno |
E13481
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Leno |
E13481
|
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: Leno | Statement: [Jay Leno, familyName, Leno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leno Context triple: [Jay Leno, familyName, Leno]
-
A.
Jay Leno
chosen
Jay Leno is an American comedian and longtime host of NBC’s “The Tonight Show,” known for his observational stand-up and prominent role in late-night television.
-
B.
David Letterman
David Letterman is an American television host and comedian best known for his long-running late-night talk shows, including "Late Night with David Letterman" and "The Late Show with David Letterman."
-
C.
Ray Romano
Ray Romano is an American stand-up comedian and actor best known for creating and starring in the hit sitcom "Everybody Loves Raymond."
-
D.
Joseph Clerico
Joseph Clerico was a French impresario best known for co-founding and developing the famed Lido de Paris cabaret into one of Paris’s most iconic nightlife institutions.
-
E.
Jim Gaffigan
Jim Gaffigan is an American stand-up comedian and actor known for his observational, family-friendly humor and roles in both film and television.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a700e608190b235246df057bd9b |
completed | March 1, 2026, 7:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4efcf05b88190a0fc2f2e86834248 |
completed | March 2, 2026, 2:02 a.m. |
Created at: March 1, 2026, 7:32 p.m.