Triple
T18248179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heartburn |
E437008
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Mike Nichols |
—
|
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: Mike Nichols | Statement: [Heartburn, director, Mike Nichols]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Nichols Context triple: [Heartburn, director, Mike Nichols]
-
A.
Mike Nichols
chosen
Mike Nichols was an acclaimed American film and theater director known for influential works like "The Graduate" and his sharp, character-driven storytelling that helped define a generation of cinema.
-
B.
Sydney Pollack
Sydney Pollack was an American film director, producer, and actor known for acclaimed movies such as "Out of Africa," "Tootsie," and "The Firm."
-
C.
Sidney Lumet
Sidney Lumet was an acclaimed American film director known for socially conscious, character-driven dramas such as "12 Angry Men," "Serpico," and "Dog Day Afternoon."
-
D.
Paul Mazursky
Paul Mazursky was an American film director, screenwriter, and actor known for his sharp, character-driven social comedies and satires in the 1960s through the 1980s.
-
E.
Arthur Hiller
Arthur Hiller was a Canadian-born film director best known for popular Hollywood movies such as "Love Story" and "The In-Laws."
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e89b288190a286797ec2cd60a8 |
completed | April 19, 2026, 3:42 p.m. |
Created at: April 10, 2026, 10:33 a.m.