Triple
T22102966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daddy (1989 film) |
E546214
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Saaransh Films
Saaransh Films is an Indian film production company known for backing Hindi-language movies such as the 1989 drama "Daddy."
|
E1524129
|
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: Saaransh Films | Statement: [Daddy (1989 film), productionCompany, Saaransh Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saaransh Films Context triple: [Daddy (1989 film), productionCompany, Saaransh Films]
-
A.
Sahai Films
Sahai Films is an Indian film production company known for producing the cult classic television film "In Which Annie Gives It Those Ones."
-
B.
Mohan Films
Mohan Films is an Indian film distribution company known for handling the release of various Hindi movies.
-
C.
R. K. Films
R. K. Films is an Indian film production company founded by legendary actor-filmmaker Raj Kapoor, known for producing several classic Hindi movies.
-
D.
Muktha Films
Muktha Films is an Indian film production company best known for producing acclaimed Tamil cinema, including the classic crime drama "Nayakan."
-
E.
Mohan Productions
Mohan Productions is a television production company best known for producing the NBC family sitcom "Lopez vs Lopez."
- 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: Saaransh Films Triple: [Daddy (1989 film), productionCompany, Saaransh Films]
Generated description
Saaransh Films is an Indian film production company known for backing Hindi-language movies such as the 1989 drama "Daddy."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saaransh Films Target entity description: Saaransh Films is an Indian film production company known for backing Hindi-language movies such as the 1989 drama "Daddy."
-
A.
Sahai Films
Sahai Films is an Indian film production company known for producing the cult classic television film "In Which Annie Gives It Those Ones."
-
B.
Mohan Films
Mohan Films is an Indian film distribution company known for handling the release of various Hindi movies.
-
C.
R. K. Films
R. K. Films is an Indian film production company founded by legendary actor-filmmaker Raj Kapoor, known for producing several classic Hindi movies.
-
D.
Muktha Films
Muktha Films is an Indian film production company best known for producing acclaimed Tamil cinema, including the classic crime drama "Nayakan."
-
E.
Mohan Productions
Mohan Productions is a television production company best known for producing the NBC family sitcom "Lopez vs Lopez."
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129175a7881909549883f23c53dca |
completed | April 28, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0aa5fe88488190b775ff282d8b4e3b |
completed | May 18, 2026, 5:39 a.m. |
| NEDg | Description generation | batch_6a0aa6930fa481909bfd0c97f4880804 |
completed | May 18, 2026, 5:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0aa7150e9c81908069369f2075dea5 |
completed | May 18, 2026, 5:43 a.m. |
Created at: April 16, 2026, 8:30 p.m.