Triple

T26190253
Position Surface form Disambiguated ID Type / Status
Subject Aït Boumahdi E654941 entity
Predicate likelySecondaryLanguage P9103 FINISHED
Object French LITERAL 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: French | Statement: [Aït Boumahdi, likelySecondaryLanguage, French]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: likelySecondaryLanguage
Context triple: [Aït Boumahdi, likelySecondaryLanguage, French]
  • A. hasSecondaryLanguage chosen
    Indicates that an entity possesses or uses a secondary language in addition to its primary language.
  • B. hasSecondaryNationalLanguage
    Indicates that an entity possesses an officially recognized secondary national language in addition to its primary national language.
  • C. laterSecondaryLanguageOfAdministration
    Indicates that one language served as a subsequent or later secondary language used for administrative purposes in relation to another language.
  • D. hasSecondaryLanguageNearby
    Indicates that an entity has at least one secondary language present or used in its immediate vicinity or surrounding context.
  • E. hasSecondaryLanguageFamily
    Indicates that an entity has an additional, non-primary association with a particular language family.
  • F. None of above.

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_69ee5b469bc081908fe486453fdad810 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f612607c388190ab61d1ac7d18e08d completed May 2, 2026, 3:04 p.m.
PD Predicate disambiguation batch_69f611a9272881909093360472be832c completed May 2, 2026, 3 p.m.
Created at: April 26, 2026, 8:44 p.m.