Triple
T14519995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Sniper |
E340625
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Jason Hall
Jason Hall is an American screenwriter and director best known for writing the acclaimed war drama film "American Sniper."
|
E1104918
|
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: Jason Hall | Statement: [American Sniper, screenwriter, Jason Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Hall Context triple: [American Sniper, screenwriter, Jason Hall]
-
A.
Tim Lebbon
Tim Lebbon is a British horror and dark fantasy author known for his original novels and film tie-in works, including the story that inspired the film "The Silence."
-
B.
Jack Carr
Jack Carr is an actor known for his role in the film "Hellgate."
-
C.
Jim Gentry
Jim Gentry is a central male character in the 1952 melodrama film "Ruby Gentry," serving as Ruby's wealthy love interest and a key figure in the story's romantic and social conflicts.
-
D.
Andrew Gross
Andrew Gross is an American author best known for his bestselling thrillers and for coauthoring several novels with James Patterson.
-
E.
M. Scott Smith
M. Scott Smith is a film editor best known for his work on the crime thriller "To Live and Die in L.A."
- 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: Jason Hall Triple: [American Sniper, screenwriter, Jason Hall]
Generated description
Jason Hall is an American screenwriter and director best known for writing the acclaimed war drama film "American Sniper."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jason Hall Target entity description: Jason Hall is an American screenwriter and director best known for writing the acclaimed war drama film "American Sniper."
-
A.
Tim Lebbon
Tim Lebbon is a British horror and dark fantasy author known for his original novels and film tie-in works, including the story that inspired the film "The Silence."
-
B.
Jack Carr
Jack Carr is an actor known for his role in the film "Hellgate."
-
C.
Jim Gentry
Jim Gentry is a central male character in the 1952 melodrama film "Ruby Gentry," serving as Ruby's wealthy love interest and a key figure in the story's romantic and social conflicts.
-
D.
Andrew Gross
Andrew Gross is an American author best known for his bestselling thrillers and for coauthoring several novels with James Patterson.
-
E.
M. Scott Smith
M. Scott Smith is a film editor best known for his work on the crime thriller "To Live and Die in L.A."
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a70b15c81908773633e989ef704 |
completed | April 14, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a4b71688190ae9ebccdc81d09f8 |
completed | May 8, 2026, 5:53 a.m. |
| NEDg | Description generation | batch_69fd7bf6b13481908307a2037d0de804 |
completed | May 8, 2026, 6 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd7ce0d8a0819083ba348412d76ee5 |
completed | May 8, 2026, 6:04 a.m. |
Created at: April 10, 2026, 1:22 a.m.