Triple
T13702743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Apache, The Bronx |
E328559
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
MLR Films
MLR Films is a film production company known for producing the 1981 crime drama "Fort Apache, The Bronx."
|
E1055304
|
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: MLR Films | Statement: [Fort Apache, The Bronx, productionCompany, MLR Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MLR Films Context triple: [Fort Apache, The Bronx, productionCompany, MLR Films]
-
A.
Maverick Films
Maverick Films is a film production company known for backing independent and genre-driven movies, including the crime comedy-drama "Gridlock'd."
-
B.
M6 Films
M6 Films is a French film production company known for backing popular international action and thriller movies.
-
C.
Overture Films
Overture Films was an American independent film production and distribution company active in the late 2000s, known for releasing a range of mid-budget and specialty films.
-
D.
Vistar Films
Vistar Films is a film production company best known for its involvement in the making of the 1985 horror-comedy classic "Fright Night."
-
E.
Beyond Films
Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
- 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: MLR Films Triple: [Fort Apache, The Bronx, productionCompany, MLR Films]
Generated description
MLR Films is a film production company known for producing the 1981 crime drama "Fort Apache, The Bronx."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MLR Films Target entity description: MLR Films is a film production company known for producing the 1981 crime drama "Fort Apache, The Bronx."
-
A.
Maverick Films
Maverick Films is a film production company known for backing independent and genre-driven movies, including the crime comedy-drama "Gridlock'd."
-
B.
M6 Films
M6 Films is a French film production company known for backing popular international action and thriller movies.
-
C.
Overture Films
Overture Films was an American independent film production and distribution company active in the late 2000s, known for releasing a range of mid-budget and specialty films.
-
D.
Vistar Films
Vistar Films is a film production company best known for its involvement in the making of the 1985 horror-comedy classic "Fright Night."
-
E.
Beyond Films
Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
- 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_69dcad162158819089280ee1e6b5c2cf |
completed | April 13, 2026, 8:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79459192c81908132ad9813d69125 |
completed | May 3, 2026, 6:30 p.m. |
| NEDg | Description generation | batch_69f79655d5f08190a3cbf3e12e2ffa67 |
completed | May 3, 2026, 6:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7972a1cf48190a1d435227414967a |
completed | May 3, 2026, 6:42 p.m. |
Created at: April 9, 2026, 9:54 p.m.