Triple
T984959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpha Dog |
E21257
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Jake Mazursky |
E115997
|
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: Jake Mazursky | Statement: [Alpha Dog, featuresCharacter, Jake Mazursky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake Mazursky Context triple: [Alpha Dog, featuresCharacter, Jake Mazursky]
-
A.
Zack Mazursky
chosen
Zack Mazursky is a fictional teenager in the crime drama film "Alpha Dog," whose kidnapping and murder are central to the movie’s plot, inspired by the real-life Nicholas Markowitz case.
-
B.
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."
-
C.
Tom Benedek
Tom Benedek is an American screenwriter best known for co-writing the science fiction film "Cocoon."
-
D.
Hal Ashby
Hal Ashby was an influential American film director and editor of the New Hollywood era, known for acclaimed, offbeat classics such as "Harold and Maude," "Shampoo," and "Being There."
-
E.
Mike Nichols
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.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac258b55908190bc5bbf1c2756482d |
completed | March 7, 2026, 1:18 p.m. |
Created at: March 1, 2026, 7:41 p.m.