Triple
T2995425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veronica Mars |
E81053
|
entity |
| Predicate | starring |
P1507
|
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: [Veronica Mars, starring, Max Greenfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Max Greenfield Context triple: [Veronica Mars, starring, 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.
Caleb McLaughlin
Caleb McLaughlin is an American actor best known for playing Lucas Sinclair in the Netflix science-fiction horror series "Stranger Things."
-
C.
Adam Kimmel
Adam Kimmel is an American cinematographer known for his work on acclaimed films such as "Capote," "Lars and the Real Girl," and "Never Let Me Go."
-
D.
Logan Marshall-Green
Logan Marshall-Green is an American actor and director known for his roles in films like "Prometheus" and "Upgrade" as well as various television series.
-
E.
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.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99f2e5888190b3346012e2578dab |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b10908cfe48190bf244d5a3dbc958b |
completed | March 11, 2026, 6:17 a.m. |
Created at: March 8, 2026, 2:59 p.m.