Triple
T1235582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sex and the City (film) |
E26539
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Aaron Zigman |
E118675
|
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: Aaron Zigman | Statement: [Sex and the City (film), musicBy, Aaron Zigman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aaron Zigman Context triple: [Sex and the City (film), musicBy, Aaron Zigman]
-
A.
Aaron Zigman
chosen
Aaron Zigman is an American composer and producer best known for his film scores on dramas and romantic films such as "The Notebook" and "John Q."
-
B.
Mitchell Hurwitz
Mitchell Hurwitz is an American television writer and producer best known for creating the critically acclaimed sitcom "Arrested Development."
-
C.
Bruce Greenwald
Bruce Greenwald is a prominent American economist and value investing expert, widely known for his teaching and writings on value investing and competitive strategy.
-
D.
David Frankel
David Frankel is an American film and television director best known for helming popular works such as "The Devil Wears Prada" and episodes of "Sex and the City."
-
E.
Jonathan Gordon
Jonathan Gordon is a film producer best known for his work on acclaimed movies such as "Silver Linings Playbook."
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf169868819090cfab7e34c40c67 |
completed | March 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc61b45748190a12e1aec029b76df |
completed | March 8, 2026, 12:43 a.m. |
Created at: March 1, 2026, 7:47 p.m.