Triple
T20620191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Song One |
E506678
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
86 Films
86 Films is a film production company known for its work on the independent musical drama "Song One."
|
E1441556
|
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: 86 Films | Statement: [Song One, productionCompany, 86 Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 86 Films Context triple: [Song One, productionCompany, 86 Films]
-
A.
Artina Films
Artina Films is a film production company known for backing notable independent and auteur-driven movies, including Tom Ford’s psychological thriller "Nocturnal Animals."
-
B.
Stray Dog Films
Stray Dog Films is a film distribution company known for handling the release of titles such as the British comedy-drama "One Night in Istanbul."
-
C.
Aries Films
Aries Films is a film distribution company known for handling the release of independent and art-house movies such as "Bad Lieutenant."
-
D.
Athos Films
Athos Films is a French film distribution company known for handling the release of notable art-house and New Wave films.
-
E.
Queen Films
Queen Films is a production company associated with the rock band Queen, involved in developing and producing film projects related to the band and its legacy.
- 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: 86 Films Triple: [Song One, productionCompany, 86 Films]
Generated description
86 Films is a film production company known for its work on the independent musical drama "Song One."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 86 Films Target entity description: 86 Films is a film production company known for its work on the independent musical drama "Song One."
-
A.
Artina Films
Artina Films is a film production company known for backing notable independent and auteur-driven movies, including Tom Ford’s psychological thriller "Nocturnal Animals."
-
B.
Stray Dog Films
Stray Dog Films is a film distribution company known for handling the release of titles such as the British comedy-drama "One Night in Istanbul."
-
C.
Aries Films
Aries Films is a film distribution company known for handling the release of independent and art-house movies such as "Bad Lieutenant."
-
D.
Athos Films
Athos Films is a French film distribution company known for handling the release of notable art-house and New Wave films.
-
E.
Queen Films
Queen Films is a production company associated with the rock band Queen, involved in developing and producing film projects related to the band and its legacy.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe0e22c81909f6efe21518e33f0 |
completed | April 20, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08bb1776588190923236057cfd1b8f |
completed | May 16, 2026, 6:44 p.m. |
| NEDg | Description generation | batch_6a08bdd076f08190a6663d891d503a29 |
completed | May 16, 2026, 6:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08be4eddbc8190b02a5b8b96ee6a29 |
completed | May 16, 2026, 6:58 p.m. |
Created at: April 16, 2026, 11:41 a.m.