Triple
T20618819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strictly Ballroom |
E506643
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
CML Films
CML Films is a film production company best known for producing Baz Luhrmann’s acclaimed Australian dance film "Strictly Ballroom."
|
E1440790
|
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: CML Films | Statement: [Strictly Ballroom, productionCompany, CML Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CML Films Context triple: [Strictly Ballroom, productionCompany, CML Films]
-
A.
MLD Films
MLD Films is a film production company known for collaborating with other studios, such as Hopscotch, to develop and produce motion picture projects.
-
B.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
C.
Cineyug Films
Cineyug Films is an Indian film production company known for backing major Bollywood projects and entertainment ventures.
-
D.
Celandine Films
Celandine Films is a film production company best known for producing the British comedy film "Monty Python’s The Meaning of Life."
-
E.
Clover Films
Clover Films is a film distribution company known for releasing international and arthouse titles in select markets.
- 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: CML Films Triple: [Strictly Ballroom, productionCompany, CML Films]
Generated description
CML Films is a film production company best known for producing Baz Luhrmann’s acclaimed Australian dance film "Strictly Ballroom."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CML Films Target entity description: CML Films is a film production company best known for producing Baz Luhrmann’s acclaimed Australian dance film "Strictly Ballroom."
-
A.
MLD Films
MLD Films is a film production company known for collaborating with other studios, such as Hopscotch, to develop and produce motion picture projects.
-
B.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
C.
Cineyug Films
Cineyug Films is an Indian film production company known for backing major Bollywood projects and entertainment ventures.
-
D.
Celandine Films
Celandine Films is a film production company best known for producing the British comedy film "Monty Python’s The Meaning of Life."
-
E.
Clover Films
Clover Films is a film distribution company known for releasing international and arthouse titles in select markets.
- 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_69e6abdf9d7c8190969247a4ae55b781 |
completed | April 20, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08bb1588a881909f7197bfc38d9e21 |
completed | May 16, 2026, 6:44 p.m. |
| NEDg | Description generation | batch_6a08bba2e85881909ae887fc5bc3121f |
completed | May 16, 2026, 6:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08bc410f008190b00bf4956d591176 |
completed | May 16, 2026, 6:49 p.m. |
Created at: April 16, 2026, 11:41 a.m.