Triple
T16095969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bullets or Ballots |
E390485
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Martin Mooney
Martin Mooney was an American screenwriter known for his work on crime and gangster films during Hollywood’s classic era.
|
E1346565
|
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: Martin Mooney | Statement: [Bullets or Ballots, screenwriter, Martin Mooney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin Mooney Context triple: [Bullets or Ballots, screenwriter, Martin Mooney]
-
A.
Darrin Mooney
Darrin Mooney is a British drummer best known for his long-time work with the rock band Primal Scream and collaborations with various other artists.
-
B.
Martin Doherty
Martin Doherty is a Scottish musician and producer best known as a member of the synth-pop band Chvrches.
-
C.
Alan Moloney
Alan Moloney is an Irish film and television producer known for his work on numerous acclaimed dramas and literary adaptations.
-
D.
Michael Maloney
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
-
E.
James Maloney
James Maloney is an actor known for appearing in the classic television series "The Twilight Zone," including the episode "A Stop at Willoughby."
- 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: Martin Mooney Triple: [Bullets or Ballots, screenwriter, Martin Mooney]
Generated description
Martin Mooney was an American screenwriter known for his work on crime and gangster films during Hollywood’s classic era.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martin Mooney Target entity description: Martin Mooney was an American screenwriter known for his work on crime and gangster films during Hollywood’s classic era.
-
A.
Darrin Mooney
Darrin Mooney is a British drummer best known for his long-time work with the rock band Primal Scream and collaborations with various other artists.
-
B.
Martin Doherty
Martin Doherty is a Scottish musician and producer best known as a member of the synth-pop band Chvrches.
-
C.
Alan Moloney
Alan Moloney is an Irish film and television producer known for his work on numerous acclaimed dramas and literary adaptations.
-
D.
Michael Maloney
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
-
E.
James Maloney
James Maloney is an actor known for appearing in the classic television series "The Twilight Zone," including the episode "A Stop at Willoughby."
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1859283008190baac96142b5c7e53 |
completed | April 17, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05759c98248190a7483912ae13b425 |
completed | May 14, 2026, 7:11 a.m. |
| NEDg | Description generation | batch_6a057718c3b48190813b5bc51f75405c |
completed | May 14, 2026, 7:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05777f51b481909a7916bc40dcfd69 |
completed | May 14, 2026, 7:19 a.m. |
Created at: April 10, 2026, 4:59 a.m.