Triple
T22105292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shankar–Jaikishan |
E546269
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | RK Films |
E905440
|
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: RK Films | Statement: [Shankar–Jaikishan, associatedWith, RK Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RK Films Context triple: [Shankar–Jaikishan, associatedWith, RK Films]
-
A.
RSA Films
RSA Films is a renowned commercial and film production company known for creating high-profile advertising campaigns and visual storytelling for global brands.
-
B.
R. K. Films
chosen
R. K. Films is an Indian film production company founded by legendary actor-filmmaker Raj Kapoor, known for producing several classic Hindi movies.
-
C.
GK Films
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.
-
D.
Rook Films
Rook Films is a British independent film production company known for its distinctive, often surreal and genre-bending movies.
-
E.
A. K. Films
A. K. Films is an Indian film production company known for producing the 1994 Hindi action drama movie "Vijaypath."
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12918d7a4819080283c287a253c9f |
completed | April 28, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a87a9a13c8190a8c9c2f9d0061934 |
completed | May 18, 2026, 3:29 a.m. |
Created at: April 16, 2026, 8:30 p.m.