Triple
T16252611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In Dubious Battle (2016 film) |
E394547
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Matt Rager
Matt Rager is a screenwriter best known for adapting classic American literature, including John Steinbeck’s works, for contemporary film.
|
E1242743
|
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: Matt Rager | Statement: [In Dubious Battle (2016 film), screenwriter, Matt Rager]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Rager Context triple: [In Dubious Battle (2016 film), screenwriter, Matt Rager]
-
A.
Matt Graver
Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
-
B.
Josh Hager
Josh Hager is an American musician and multi-instrumentalist best known as a later-era member of the new wave band Devo.
-
C.
Brant Daugherty
Brant Daugherty is an American actor known for his roles in television series like "Pretty Little Liars" and films including the "Fifty Shades" franchise.
-
D.
Matt Luber
Matt Luber is a film producer best known for his work on the action-thriller movie "Into the Blue."
-
E.
Brian Routh
Brian Routh was a British performance artist and musician best known as one half of the avant-garde comedy and performance duo The Kipper Kids.
- 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: Matt Rager Triple: [In Dubious Battle (2016 film), screenwriter, Matt Rager]
Generated description
Matt Rager is a screenwriter best known for adapting classic American literature, including John Steinbeck’s works, for contemporary film.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matt Rager Target entity description: Matt Rager is a screenwriter best known for adapting classic American literature, including John Steinbeck’s works, for contemporary film.
-
A.
Matt Graver
Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
-
B.
Josh Hager
Josh Hager is an American musician and multi-instrumentalist best known as a later-era member of the new wave band Devo.
-
C.
Brant Daugherty
Brant Daugherty is an American actor known for his roles in television series like "Pretty Little Liars" and films including the "Fifty Shades" franchise.
-
D.
Matt Luber
Matt Luber is a film producer best known for his work on the action-thriller movie "Into the Blue."
-
E.
Brian Routh
Brian Routh was a British performance artist and musician best known as one half of the avant-garde comedy and performance duo The Kipper Kids.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24597b74481908fdb8175628a57a1 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d447f5cc81908757869f2d1e94a1 |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d55f665c8190bd9a4bf594d0bac4 |
completed | May 10, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d5c38a1081909e13c016f21899d2 |
completed | May 10, 2026, 7 p.m. |
Created at: April 10, 2026, 5:04 a.m.