Triple

T18365798
Position Surface form Disambiguated ID Type / Status
Subject الجهراء E440042 entity
Predicate officialLanguage P236 FINISHED
Object اللغة العربية NE NERFINISHED

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: اللغة العربية | Statement: [الجهراء, officialLanguage, اللغة العربية]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: اللغة العربية
Context triple: [الجهراء, officialLanguage, اللغة العربية]
  • A. Arabic chosen
    Arabic is a Semitic language widely spoken across the Arab world and used as a liturgical language in Islam.
  • B. al-Lughāt
    al-Lughāt is a significant early Arabic linguistic work by the grammarian Al-Farrāʾ, focusing on vocabulary, dialectal usage, and philological analysis.
  • C. Arabhi
    Arabhi is a bright and energetic Carnatic raga, often used in devotional compositions and known for its auspicious, uplifting character.
  • D. Lisān al-ʿArab
    Lisān al-ʿArab is a monumental 13th-century Arabic dictionary by Ibn Manẓūr, renowned as one of the most comprehensive and authoritative works on classical Arabic vocabulary and usage.
  • E. Persian language
    Persian language is a major modern Iranian language spoken primarily in Iran, Afghanistan, and Tajikistan, known for its rich literary tradition and historical influence across the Middle East and Central Asia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5174d31608190851a5bab6878c203 completed April 19, 2026, 5:56 p.m.
Created at: April 10, 2026, 10:38 a.m.