Triple
T19521366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crossroads |
E488407
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Zomba Films
Zomba Films is a film production company best known for producing the 2002 Britney Spears movie "Crossroads."
|
E1379879
|
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: Zomba Films | Statement: [Crossroads, productionCompany, Zomba Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zomba Films Context triple: [Crossroads, productionCompany, Zomba Films]
-
A.
Zomba Productions
Zomba Productions was a production and publishing arm of the Zomba music group, involved in developing and producing recordings for a variety of artists.
-
B.
Zaftig Films
Zaftig Films is a television and film production company best known for producing the acclaimed drama series "This Is Us."
-
C.
Swaka Films
Swaka Films is a film production company known for producing the 2013 adaptation of "Romeo & Juliet."
-
D.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
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: Zomba Films Triple: [Crossroads, productionCompany, Zomba Films]
Generated description
Zomba Films is a film production company best known for producing the 2002 Britney Spears movie "Crossroads."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zomba Films Target entity description: Zomba Films is a film production company best known for producing the 2002 Britney Spears movie "Crossroads."
-
A.
Zomba Productions
Zomba Productions was a production and publishing arm of the Zomba music group, involved in developing and producing recordings for a variety of artists.
-
B.
Zaftig Films
Zaftig Films is a television and film production company best known for producing the acclaimed drama series "This Is Us."
-
C.
Swaka Films
Swaka Films is a film production company known for producing the 2013 adaptation of "Romeo & Juliet."
-
D.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635a0b37c8190b70b7427c2e85f59 |
completed | April 20, 2026, 2:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07472af0b881909e5bada0955b52bb |
completed | May 15, 2026, 4:17 p.m. |
| NEDg | Description generation | batch_6a0747f6b1d48190a3e70576ddb4feb2 |
completed | May 15, 2026, 4:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07492428bc819084dad08d711679a5 |
completed | May 15, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:40 p.m.