Triple

T8340928
Position Surface form Disambiguated ID Type / Status
Subject Goutam Ghose E195910 entity
Predicate name P16 FINISHED
Object Goutam Ghose E195910 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: Goutam Ghose | Statement: [Goutam Ghose, name, Goutam Ghose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Goutam Ghose
Context triple: [Goutam Ghose, name, Goutam Ghose]
  • A. Goutam Ghose chosen
    Goutam Ghose is an acclaimed Indian filmmaker and cinematographer known for his socially conscious and visually poetic works in Bengali and parallel cinema.
  • B. Amlānand Ghosh
    Amlānand Ghosh was an Indian archaeologist noted for his pioneering work on Indus Valley Civilization sites, including the early excavation and identification of Kalibangan.
  • C. Rabi Ghosh
    Rabi Ghosh was a renowned Indian Bengali actor and comedian, celebrated for his memorable character roles in classic films and his long association with director Satyajit Ray.
  • D. Bhudev Mukhopadhyay
    Bhudev Mukhopadhyay was a 19th-century Bengali writer, educator, and social thinker known for his contributions to early modern Bengali literature and intellectual life.
  • E. Jnanesh Mukherjee
    Jnanesh Mukherjee is an Indian actor known for his work in Bengali cinema and television.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fe8989481909b32d4bfd586372d completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cebb37161081908452cc449b4e903e completed April 2, 2026, 6:53 p.m.
Created at: March 30, 2026, 5:57 p.m.