Triple
T8669686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Town |
E205762
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | GK Films |
E130832
|
NE FINISHED |
How this triple was built (2 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: GK Films | Statement: [The Town, productionCompany, GK Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GK Films Context triple: [The Town, productionCompany, GK Films]
-
A.
GK Films
chosen
GK Films is a British-American production company founded by producer Graham King, known for backing acclaimed films such as Argo, The Departed, and Bohemian Rhapsody.
-
B.
Muktha Films
Muktha Films is an Indian film production company best known for producing acclaimed Tamil cinema, including the classic crime drama "Nayakan."
-
C.
Misher Films
Misher Films is an American film production company known for producing a range of mainstream Hollywood movies, including the biographical sports comedy-drama "Fighting with My Family."
-
D.
GV Films
GV Films is an Indian film production and distribution company known for backing several notable Tamil and South Indian movies.
-
E.
SKA Films
SKA Films is a British film production company co-founded by director Matthew Vaughn, known for producing stylish crime and action movies such as "Layer Cake."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4917cb9881909a73b74e54250613 |
completed | March 31, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3898bf88190959b361638d032de |
completed | April 2, 2026, 10:54 p.m. |
Created at: March 30, 2026, 6:31 p.m.