Triple

T16183602
Position Surface form Disambiguated ID Type / Status
Subject Taare Zameen Par E392743 entity
Predicate cinematographer P1953 FINISHED
Object Setu
Setu is an Indian cinematographer best known for his acclaimed visual work on the film *Taare Zameen Par* and other notable Hindi movies.
E1199425 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: Setu | Statement: [Taare Zameen Par, cinematographer, Setu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Setu
Context triple: [Taare Zameen Par, cinematographer, Setu]
  • A. Nivedita Setu
    Nivedita Setu is a modern cable-stayed bridge in West Bengal, India, named after Sister Nivedita and serving as a key roadway link near Kolkata.
  • B. Sudama Setu
    Sudama Setu is a pedestrian suspension bridge in Dwarka, Gujarat, that connects the mainland near the Dwarkadhish Temple to the sacred Panchkui beach across the Gomti creek.
  • C. Ghatere
    Ghatere is a settlement located on the island of Kolombangara in the Solomon Islands.
  • D. Gaighata
    Gaighata is a town in the North 24 Parganas district of West Bengal, India, known for its semi-rural character and proximity to the India–Bangladesh border.
  • E. Tarang
    Tarang is a prominent musical composition by Indian tabla virtuoso Sandeep Das, showcasing his innovative approach to Indian classical rhythm.
  • 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: Setu
Triple: [Taare Zameen Par, cinematographer, Setu]
Generated description
Setu is an Indian cinematographer best known for his acclaimed visual work on the film *Taare Zameen Par* and other notable Hindi movies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Setu
Target entity description: Setu is an Indian cinematographer best known for his acclaimed visual work on the film *Taare Zameen Par* and other notable Hindi movies.
  • A. Nivedita Setu
    Nivedita Setu is a modern cable-stayed bridge in West Bengal, India, named after Sister Nivedita and serving as a key roadway link near Kolkata.
  • B. Sudama Setu
    Sudama Setu is a pedestrian suspension bridge in Dwarka, Gujarat, that connects the mainland near the Dwarkadhish Temple to the sacred Panchkui beach across the Gomti creek.
  • C. Ghatere
    Ghatere is a settlement located on the island of Kolombangara in the Solomon Islands.
  • D. Gaighata
    Gaighata is a town in the North 24 Parganas district of West Bengal, India, known for its semi-rural character and proximity to the India–Bangladesh border.
  • E. Tarang
    Tarang is a prominent musical composition by Indian tabla virtuoso Sandeep Das, showcasing his innovative approach to Indian classical rhythm.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205fc080819097858f36253fef7c completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffff03400481908e66db8cf0213c15 completed May 10, 2026, 3:44 a.m.
NEDg Description generation batch_6a0000ceba648190ac5ecefd34f10d4e completed May 10, 2026, 3:51 a.m.
NED2 Entity disambiguation (via description) batch_6a00013fdb1c8190add653fc1cf30e44 completed May 10, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:02 a.m.