Triple
T14173685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mortdecai |
E351276
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Eric Aronson
Eric Aronson is an American screenwriter and film producer best known for writing the action-comedy film "Mortdecai."
|
E1123010
|
NE FINISHED |
How this triple was built (4 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: Eric Aronson | Statement: [Mortdecai, screenwriter, Eric Aronson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Aronson Context triple: [Mortdecai, screenwriter, Eric Aronson]
-
A.
John Aronson
John Aronson is a cinematographer best known for his work on the World War II aviation film "Red Tails."
-
B.
Michael Fishman
Michael Fishman is an American actor best known for playing D.J. Conner on the long-running sitcom "Roseanne" and its revival.
-
C.
Andrew Rona
Andrew Rona is an American film producer and studio executive known for his work on genre and action-thriller films.
-
D.
Daniel Ullman
Daniel Ullman was an American screenwriter known for his work on mid-20th-century genre films, particularly Westerns and thrillers.
-
E.
Eric Tannenbaum
Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Eric Aronson Triple: [Mortdecai, screenwriter, Eric Aronson]
Generated description
Eric Aronson is an American screenwriter and film producer best known for writing the action-comedy film "Mortdecai."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eric Aronson Target entity description: Eric Aronson is an American screenwriter and film producer best known for writing the action-comedy film "Mortdecai."
-
A.
John Aronson
John Aronson is a cinematographer best known for his work on the World War II aviation film "Red Tails."
-
B.
Michael Fishman
Michael Fishman is an American actor best known for playing D.J. Conner on the long-running sitcom "Roseanne" and its revival.
-
C.
Andrew Rona
Andrew Rona is an American film producer and studio executive known for his work on genre and action-thriller films.
-
D.
Daniel Ullman
Daniel Ullman was an American screenwriter known for his work on mid-20th-century genre films, particularly Westerns and thrillers.
-
E.
Eric Tannenbaum
Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
- F. None of above. chosen
Provenance (5 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b7cc3081909f4fa371e1eae130 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe387f28688190b9d20f1e2bbc0ddc |
completed | May 8, 2026, 7:24 p.m. |
| NEDg | Description generation | batch_69fe6128b2948190988aea647d54426e |
completed | May 8, 2026, 10:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe617af4a881908a906c34995d2403 |
completed | May 8, 2026, 10:19 p.m. |
Created at: April 10, 2026, 1:01 a.m.