Triple
T14751179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulholland Drive |
E346608
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Mary Sweeney |
E1178691
|
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: Mary Sweeney | Statement: [Mulholland Drive, producer, Mary Sweeney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Sweeney Context triple: [Mulholland Drive, producer, Mary Sweeney]
-
A.
Mary Sweeney
chosen
Mary Sweeney is an American film editor, producer, and writer best known for her long-time collaboration with director David Lynch on projects such as "Lost Highway" and "Mulholland Drive."
-
B.
Maureen Sweeney
Maureen Sweeney is an Irish woman best known for her crucial World War II weather observations that influenced the timing of the D-Day landings.
-
C.
Ann Sweeny
Ann Sweeny is best known as the wife of acclaimed American television producer, director, and writer Gene Reynolds.
-
D.
Sarah Sweeney
Sarah Sweeney is an actress known for her role in the historical drama television series "The Bastard Executioner."
-
E.
Sarah O’Meara
Sarah O’Meara is known as the spouse of Australian film director Paul Cox.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d40efc8190bb1be34c19a2b57c |
completed | April 14, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009181980481908fb49e464aef8734 |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:30 a.m.