Triple

T8527985
Position Surface form Disambiguated ID Type / Status
Subject Prosenjit Chatterjee E201866 entity
Predicate notableWork P4 FINISHED
Object Dosar E694838 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: Dosar | Statement: [Prosenjit Chatterjee, notableWork, Dosar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dosar
Context triple: [Prosenjit Chatterjee, notableWork, Dosar]
  • A. Dosar chosen
    Dosar is a 2006 Bengali drama film directed by Rituparno Ghosh that explores complex marital relationships and emotional infidelity.
  • B. Les Dingodossiers
    Les Dingodossiers is a French comic series blending absurd humor and satirical short stories, created in the 1960s by René Goscinny and Gotlib.
  • C. L’Affaire
    L’Affaire is a comic novel by Diane Johnson that satirizes American and European cultural clashes through a mystery set in the French Alps.
  • D. The Summons
    The Summons is a legal thriller novel by John Grisham that follows a law professor who uncovers a mysterious stash of cash among his late father's belongings, drawing him into danger and intrigue.
  • E. Olay
    Olay is a popular global skincare brand known for its anti-aging creams, moisturizers, and facial care products.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe672e0588190a84328e1bf974f08 completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d54ef908190970a1010c8018abd completed April 2, 2026, 1:21 p.m.
Created at: March 30, 2026, 6:17 p.m.