Triple
T16636295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AGBO |
E404212
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
AGBO Films
AGBO Films is an American film and television production company founded by directors Anthony and Joe Russo, known for producing high-profile genre and blockbuster projects.
|
E1224433
|
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: AGBO Films | Statement: [AGBO, alsoKnownAs, AGBO Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AGBO Films Context triple: [AGBO, alsoKnownAs, AGBO Films]
-
A.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
B.
Athos Films
Athos Films is a French film distribution company known for handling the release of notable art-house and New Wave films.
-
C.
Aquarius Films
Aquarius Films is an Australian film and television production company known for creating distinctive, character-driven screen content for both local and international audiences.
-
D.
Cineyug Films
Cineyug Films is an Indian film production company known for backing major Bollywood projects and entertainment ventures.
-
E.
Ombra Films
Ombra Films is a film production company known for working on action and thriller movies, including the crime thriller "Run All Night."
- 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: AGBO Films Triple: [AGBO, alsoKnownAs, AGBO Films]
Generated description
AGBO Films is an American film and television production company founded by directors Anthony and Joe Russo, known for producing high-profile genre and blockbuster projects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AGBO Films Target entity description: AGBO Films is an American film and television production company founded by directors Anthony and Joe Russo, known for producing high-profile genre and blockbuster projects.
-
A.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
B.
Athos Films
Athos Films is a French film distribution company known for handling the release of notable art-house and New Wave films.
-
C.
Aquarius Films
Aquarius Films is an Australian film and television production company known for creating distinctive, character-driven screen content for both local and international audiences.
-
D.
Cineyug Films
Cineyug Films is an Indian film production company known for backing major Bollywood projects and entertainment ventures.
-
E.
Ombra Films
Ombra Films is a film production company known for working on action and thriller movies, including the crime thriller "Run All Night."
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378ea4b848190bf7c95dad8a855f0 |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007dc28df48190b01c1328df24df60 |
completed | May 10, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_6a007e8cff9881908c6b86da38fc2f08 |
completed | May 10, 2026, 12:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007f53918481908d84ecf50a562266 |
completed | May 10, 2026, 12:51 p.m. |
Created at: April 10, 2026, 5:17 a.m.