Triple
T13687084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zaytoun |
E328158
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Eagle Films
Eagle Films is a film production company known for backing cinematic projects such as the war drama "Zaytoun."
|
E1054444
|
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: Eagle Films | Statement: [Zaytoun, productionCompany, Eagle Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eagle Films Context triple: [Zaytoun, productionCompany, Eagle Films]
-
A.
Hawk Films
Hawk Films was a British film production company best known for producing several of Stanley Kubrick’s films, including "The Shining."
-
B.
Eagle-Lion Films
Eagle-Lion Films was an American film production and distribution company active in the late 1940s, best known for its low-budget features and notable film noir titles.
-
C.
Kestrel Films
Kestrel Films is a British film production company best known for producing Ken Loach’s acclaimed 1969 drama "Kes."
-
D.
Echo Films
Echo Films is a film and television production company co-founded by Jennifer Aniston, known for producing character-driven projects including the series "The Morning Show."
-
E.
Sunrise Films
Sunrise Films is a film distribution company known for handling the release of independent and international movies such as "Dinner Rush."
- 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: Eagle Films Triple: [Zaytoun, productionCompany, Eagle Films]
Generated description
Eagle Films is a film production company known for backing cinematic projects such as the war drama "Zaytoun."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eagle Films Target entity description: Eagle Films is a film production company known for backing cinematic projects such as the war drama "Zaytoun."
-
A.
Hawk Films
Hawk Films was a British film production company best known for producing several of Stanley Kubrick’s films, including "The Shining."
-
B.
Eagle-Lion Films
Eagle-Lion Films was an American film production and distribution company active in the late 1940s, best known for its low-budget features and notable film noir titles.
-
C.
Kestrel Films
Kestrel Films is a British film production company best known for producing Ken Loach’s acclaimed 1969 drama "Kes."
-
D.
Echo Films
Echo Films is a film and television production company co-founded by Jennifer Aniston, known for producing character-driven projects including the series "The Morning Show."
-
E.
Sunrise Films
Sunrise Films is a film distribution company known for handling the release of independent and international movies such as "Dinner Rush."
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc670968881908e2b4fdf656c7285 |
completed | April 12, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944981ec8190be5ff39b7c2c70ab |
completed | May 3, 2026, 6:30 p.m. |
| NEDg | Description generation | batch_69f795e361c48190b37060312e7df181 |
completed | May 3, 2026, 6:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f796e5c60c8190a19389bc4cdbd658 |
completed | May 3, 2026, 6:41 p.m. |
Created at: April 9, 2026, 9:53 p.m.