Triple

T7011708
Position Surface form Disambiguated ID Type / Status
Subject Bernard Sasia E162597 entity
Predicate notableWork P4 FINISHED
Object Monsieur Ibrahim E29833 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: Monsieur Ibrahim | Statement: [Bernard Sasia, notableWork, Monsieur Ibrahim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monsieur Ibrahim
Context triple: [Bernard Sasia, notableWork, Monsieur Ibrahim]
  • A. Monsieur Ibrahim chosen
    Monsieur Ibrahim is a 2003 French drama film in which Omar Sharif delivers an acclaimed performance as a wise Turkish shopkeeper who befriends a lonely Parisian boy.
  • B. Mr. Arabin
    Mr. Arabin is a clergyman and academic who becomes a central romantic interest in Anthony Trollope’s novel "Barchester Towers."
  • C. Mounir
    Mounir is a masculine given name of Arabic origin, commonly used in various Arabic-speaking and Muslim-majority countries.
  • D. Saïd
    Saïd is a masculine given name of Arabic origin, commonly used in various forms across the Middle East and North Africa.
  • E. Moor Zogoiby
    Moor Zogoiby is a central character in Salman Rushdie’s novel "The Moor’s Last Sigh," a deformed, fast-talking Bombay-born narrator whose life and family saga reflect the tumultuous history and cultural hybridity of modern India.
  • 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_69c6885a127c8190867b059bdccf13ff completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc5729448190af66dbd6f3e8936e completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a4bd424819097e1543ec59979ff completed March 28, 2026, 5:42 a.m.
Created at: March 27, 2026, 2:34 p.m.