Triple
T597898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fist Fight |
E11426
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Max Greenfield |
E77663
|
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: Max Greenfield | Statement: [Fist Fight, screenwriter, Max Greenfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Max Greenfield Context triple: [Fist Fight, screenwriter, Max Greenfield]
-
A.
Max Greenfield
chosen
Max Greenfield is an American actor best known for his role as Schmidt on the television sitcom "New Girl."
-
B.
Matthew Macfadyen
Matthew Macfadyen is an English actor known for his versatile performances in film and television, including prominent roles in "Pride & Prejudice," "Succession," and various British dramas.
-
C.
Zach Staenberg
Zach Staenberg is an American film editor best known for his Academy Award–winning work on "The Matrix" and its sequels.
-
D.
Neil Patrick Harris
Neil Patrick Harris is an American actor, comedian, and magician best known for his roles in the TV series "How I Met Your Mother" and "Doogie Howser, M.D."
-
E.
Noah Keen
Noah Keen was a British character actor known for his numerous supporting roles in film and television from the 1950s through the 1990s.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d776c6c819081b41a9b55041cd5 |
completed | March 1, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a566fce9808190931b7c88b5c5686f |
completed | March 2, 2026, 10:31 a.m. |
Created at: March 1, 2026, 7:35 p.m.