Triple

T27904363
Position Surface form Disambiguated ID Type / Status
Subject Asia/Jerusalem E705725 entity
Predicate secondaryLanguageEnvironment P9103 FINISHED
Object Arabic 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: Arabic | Statement: [Asia/Jerusalem, secondaryLanguageEnvironment, Arabic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: secondaryLanguageEnvironment
Context triple: [Asia/Jerusalem, secondaryLanguageEnvironment, Arabic]
  • A. secondaryLanguageContext
    Indicates that the associated information, interaction, or content occurs within or is tailored to a secondary (non-primary) language setting or usage context.
  • B. laterSecondaryLanguageOfAdministration
    Indicates that one language served as a subsequent or later secondary language used for administrative purposes in relation to another language.
  • C. nationalLanguageEnvironment
    Indicates the relationship between a country or region and the language(s) that function as the primary or officially recognized means of communication in that environment.
  • D. suffixLanguage
    Indicates that one language is used as a suffix or ending element in the formation or representation of another language or linguistic expression.
  • E. hasSecondaryLanguage chosen
    Indicates that an entity possesses or uses a secondary language in addition to its primary language.
  • 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_69ef96b5aad08190be36a277c31e7004 completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69fb2e940d5c8190bceae77daf4ef512 completed May 6, 2026, 12:05 p.m.
PD Predicate disambiguation batch_69f9fec70bd881909c658a3c5020318b completed May 5, 2026, 2:29 p.m.
Created at: April 27, 2026, 6:44 p.m.