Triple
T16256941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Designing Woman |
E394654
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Adrienne Fazan |
—
|
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: Adrienne Fazan | Statement: [Designing Woman, editedBy, Adrienne Fazan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adrienne Fazan Context triple: [Designing Woman, editedBy, Adrienne Fazan]
-
A.
Adrienne Fazan
chosen
Adrienne Fazan was an American film editor best known for her long collaboration with MGM and director Vincente Minnelli, including work on classic Hollywood musicals.
-
B.
Joanna Adler
Joanna Adler is an American actress known for her work in film, television, and theater, including a role in the musical drama film "Tick, Tick... Boom!".
-
C.
Reneé Seitchek
Reneé Seitchek is the central protagonist of the novel "Strong Motion," around whom the story’s events and themes revolve.
-
D.
Debra Frisch
Debra Frisch is an American former psychology professor and blogger best known for a high-profile online harassment case involving a political commentator.
-
E.
Fiona Gubelmann
Fiona Gubelmann is an American actress best known for her role as Dr. Morgan Reznick on the medical drama series "The Good Doctor."
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2459b1624819086bf681075097235 |
completed | April 17, 2026, 2:37 p.m. |
Created at: April 10, 2026, 5:04 a.m.