Triple

T4271500
Position Surface form Disambiguated ID Type / Status
Subject Khorasani Turkic E96949 entity
Predicate hasLoanwordsFrom P506 FINISHED
Object Arabic 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 | Statement: [Khorasani Turkic, hasLoanwordsFrom, Arabic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arabic
Context triple: [Khorasani Turkic, hasLoanwordsFrom, Arabic]
  • A. Arabic chosen
    Arabic is a Semitic language widely spoken across the Arab world and used as a liturgical language in Islam.
  • B. Hijazi Arabic
    Hijazi Arabic is a major regional variety of Arabic spoken primarily in western Saudi Arabia, especially in the Hijaz region including cities like Mecca, Medina, and Jeddah.
  • C. 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.
  • D. Hassaniya Arabic
    Hassaniya Arabic is a variety of Arabic spoken primarily in Mauritania and parts of neighboring West African and Saharan countries, known for its Bedouin roots and distinctive phonology and vocabulary.
  • E. Egyptian Arabic
    Egyptian Arabic is the most widely understood modern Arabic dialect, centered in Egypt and heavily influenced by the speech and media of Cairo.
  • 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_69b34543f06c8190915ebb1a4574ffa9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ffce3d8819083d2278547fa52c1 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7a7fbe0819080076b8d8e4c3bbe completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:07 p.m.