Triple

T2747557
Position Surface form Disambiguated ID Type / Status
Subject Saint-Nazaire E60904 entity
Predicate hasDemonym P191 FINISHED
Object Nazairienne E296133 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: Nazairienne | Statement: [Saint-Nazaire, hasDemonym, Nazairienne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nazairienne
Context triple: [Saint-Nazaire, hasDemonym, Nazairienne]
  • A. Nazairien chosen
    Nazairien is the French demonym for an inhabitant of the coastal city of Saint-Nazaire in western France.
  • B. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • C. Nabawiyya
    Nabawiyya is a character in Naguib Mahfouz’s novel "The Thief and the Dogs," known primarily as the unfaithful wife whose betrayal deeply impacts the protagonist, Said Mahran.
  • D. Sawalha
    Sawalha is a family name most notably associated with British actresses Julia and Nadia Sawalha.
  • E. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • 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_69ab4b79846081909096725374d65ce9 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb4ff7b08190b72edb6a2bc5fd19 completed March 7, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc03bd03881908747845aede53f83 completed March 10, 2026, 6:54 a.m.
Created at: March 6, 2026, 9:56 p.m.