Triple

T2101603
Position Surface form Disambiguated ID Type / Status
Subject Turkic languages E37102 entity
Predicate areInfluencedBy P25489 FINISHED
Object Arabic (lexicon) E1330 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: Arabic (lexicon) | Statement: [Turkic languages, areInfluencedBy, Arabic (lexicon)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arabic (lexicon)
Context triple: [Turkic languages, areInfluencedBy, Arabic (lexicon)]
  • A. Arabic chosen
    Arabic is a Semitic language widely spoken across the Arab world and used as a liturgical language in Islam.
  • B. Arabic Supplement
    Arabic Supplement is a Unicode block that contains additional Arabic script characters used for extended orthographic and contextual purposes beyond the basic Arabic block.
  • C. Arabic alphabet
    The Arabic alphabet is a cursive, right-to-left abjad script used across the Arab world and adapted for many other languages, including Persian, Urdu, and Pashto.
  • D. Najdi Arabic
    Najdi Arabic is a central Arabian dialect of the Arabic language spoken primarily in the Najd region of Saudi Arabia.
  • E. Badawi Najdi Arabic
    Badawi Najdi Arabic is a Bedouin variety of the Najdi Arabic dialect spoken primarily by nomadic and tribal communities in central Arabia.
  • 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_69a8861828948190924aa30c08806b3a completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abbabc83a8819091f786f21d33b5a6 completed March 7, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae3065f3588190bc483e07dda8cf71 completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:43 p.m.