Triple
T21110959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garm Hava |
E520168
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Ishan Arya
Ishan Arya was an Indian cinematographer best known for his influential work in parallel cinema, particularly in landmark films of the 1970s.
|
E1471627
|
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: Ishan Arya | Statement: [Garm Hava, cinematographyBy, Ishan Arya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ishan Arya Context triple: [Garm Hava, cinematographyBy, Ishan Arya]
-
A.
Ishaan Awasthi
Ishaan Awasthi is the dyslexic young boy at the heart of the Indian film "Taare Zameen Par," whose struggles and artistic talent highlight the challenges faced by children with learning disabilities.
-
B.
Akash Khurana
Akash Khurana is an Indian actor, screenwriter, and director known for his work in Hindi cinema and television.
-
C.
Vivaan Shah
Vivaan Shah is an Indian film actor known for his roles in Hindi cinema and as the son of acclaimed actor Naseeruddin Shah.
-
D.
Varun Krishna
Varun Krishna is a business executive known for his leadership role at Rocket Companies, Inc., a major U.S.-based fintech and mortgage lending firm.
-
E.
Raghav Bhalla
Raghav Bhalla is an individual notable enough to be specifically cited as a bearer of the Bhalla surname.
- 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: Ishan Arya Triple: [Garm Hava, cinematographyBy, Ishan Arya]
Generated description
Ishan Arya was an Indian cinematographer best known for his influential work in parallel cinema, particularly in landmark films of the 1970s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ishan Arya Target entity description: Ishan Arya was an Indian cinematographer best known for his influential work in parallel cinema, particularly in landmark films of the 1970s.
-
A.
Ishaan Awasthi
Ishaan Awasthi is the dyslexic young boy at the heart of the Indian film "Taare Zameen Par," whose struggles and artistic talent highlight the challenges faced by children with learning disabilities.
-
B.
Akash Khurana
Akash Khurana is an Indian actor, screenwriter, and director known for his work in Hindi cinema and television.
-
C.
Vivaan Shah
Vivaan Shah is an Indian film actor known for his roles in Hindi cinema and as the son of acclaimed actor Naseeruddin Shah.
-
D.
Varun Krishna
Varun Krishna is a business executive known for his leadership role at Rocket Companies, Inc., a major U.S.-based fintech and mortgage lending firm.
-
E.
Raghav Bhalla
Raghav Bhalla is an individual notable enough to be specifically cited as a bearer of the Bhalla surname.
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72101f7308190beb202a052ff04d2 |
completed | April 21, 2026, 7:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a097eb949588190ad325357a3df9251 |
completed | May 17, 2026, 8:39 a.m. |
| NEDg | Description generation | batch_6a097f7635f08190bf9552d4aa05063e |
completed | May 17, 2026, 8:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a098037ffa4819095b1482d6bd83583 |
completed | May 17, 2026, 8:45 a.m. |
Created at: April 16, 2026, 2:54 p.m.