Triple
T12225079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Party |
E291327
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Tom Waldman |
E924962
|
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: Tom Waldman | Statement: [The Party, writer, Tom Waldman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Waldman Context triple: [The Party, writer, Tom Waldman]
-
A.
Tom Waldman
chosen
Tom Waldman is an author and writer known for his work on the book "High Time."
-
B.
Jeff Weltman
Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
-
C.
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.
-
D.
Jim Manzi
Jim Manzi is an American businessman best known for leading Lotus Development Corporation as its CEO during the height of its success in the software industry.
-
E.
Frank Whaley
Frank Whaley is an American actor, director, and screenwriter known for his roles in films such as "Pulp Fiction," "Swimming with Sharks," and numerous independent movies.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ca11f788190bad2efb6c83ffccb |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aa9023881909f8373e02d2cad4b |
completed | May 2, 2026, 2:31 p.m. |
Created at: April 8, 2026, 9:51 p.m.