Triple
T19948632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sabrina (1995 film) |
E479494
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Sydney Pollack |
—
|
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: Sydney Pollack | Statement: [Sabrina (1995 film), director, Sydney Pollack]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sydney Pollack Context triple: [Sabrina (1995 film), director, Sydney Pollack]
-
A.
Sydney Pollack
chosen
Sydney Pollack was an American film director, producer, and actor known for acclaimed movies such as "Out of Africa," "Tootsie," and "The Firm."
-
B.
Arthur Hiller
Arthur Hiller was a Canadian-born film director best known for popular Hollywood movies such as "Love Story" and "The In-Laws."
-
C.
Michael Cimino
Michael Cimino is an American actor best known for starring as Victor Salazar in the Hulu/Disney+ teen drama series "Love, Victor."
-
D.
Michael Cimino
Michael Cimino was an American film director and screenwriter best known for his ambitious, visually striking dramas and his Oscar-winning work on the Vietnam War epic "The Deer Hunter."
-
E.
Barry Levinson
Barry Levinson is an American filmmaker and screenwriter best known for directing acclaimed films such as "Rain Man," "Diner," and "Good Morning, Vietnam."
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a69ae388190918e862012f9fe39 |
completed | April 20, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:54 p.m.