Triple
T22846965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revenge of the Pink Panther |
E566247
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Tom Waldman |
—
|
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: Tom Waldman | Statement: [Revenge of the Pink Panther, screenwriter, Tom Waldman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Waldman Context triple: [Revenge of the Pink Panther, screenwriter, Tom Waldman]
-
A.
Tom Waldman
chosen
Tom Waldman was an American screenwriter best known for his work on comedy films and television, including contributions to the Pink Panther series.
-
B.
Tom Waldman
Tom Waldman is an author and writer known for his work on the book "High Time."
-
C.
Jeff Weltman
Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
-
D.
Jay Wadley
Jay Wadley is an American composer known for his evocative film scores and work on independent and arthouse cinema.
-
E.
Ed Vargo
Ed Vargo was a prominent Major League Baseball umpire who worked in the National League for over two decades and officiated multiple World Series and All-Star Games.
- 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_69e2458750b481908a8e4cf4609cc6cf |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e88fb408190a58c91486ea65169 |
completed | April 29, 2026, 3:44 a.m. |
Created at: April 17, 2026, 3:36 p.m.