Triple

T7772368
Position Surface form Disambiguated ID Type / Status
Subject Kamal Haasan E179101 entity
Predicate notableWork P4 FINISHED
Object Saagar E528617 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: Saagar | Statement: [Kamal Haasan, notableWork, Saagar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saagar
Context triple: [Kamal Haasan, notableWork, Saagar]
  • A. Saagar chosen
    Saagar is a 1985 Hindi romantic drama film, directed by Ramesh Sippy, that is widely acclaimed for its performances by Dimple Kapadia, Rishi Kapoor, and Kamal Haasan and its memorable music by R.D. Burman.
  • B. Sagar
    Sagar is a prominent city in central India known for its educational institutions, historical significance, and role as an administrative and commercial hub in Madhya Pradesh.
  • C. Thalay Sagar
    Thalay Sagar is a prominent and technically challenging Himalayan peak in the Garhwal region of Uttarakhand, India, renowned among mountaineers for its steep rock and ice faces.
  • D. Samudra
    Samudra is the given name of Samudragupta, the renowned Gupta emperor celebrated for his military conquests and patronage of arts in ancient India.
  • E. Saaransh
    Saaransh is a critically acclaimed 1984 Hindi drama film, best known for featuring Anupam Kher in a powerful early lead role as an elderly father coping with loss.
  • 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c7046048688190a6cbc64e82b58eca completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7ee407881908e591d216c504b24 completed March 29, 2026, 6:34 a.m.
Created at: March 27, 2026, 4:11 p.m.