Triple

T340819
Position Surface form Disambiguated ID Type / Status
Subject Hausa E6832 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: [Hausa, hasLoanwordsFrom, Arabic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arabic
Context triple: [Hausa, 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. 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.
  • D. Mesopotamian Arabic
    Mesopotamian Arabic is a major variety of Arabic spoken primarily in Iraq and neighboring regions, characterized by distinctive phonological and grammatical features that set it apart from other Arabic dialects.
  • E. Gulf Arabic
    Gulf Arabic is a regional variety of the Arabic language spoken primarily in the countries bordering the Persian Gulf, characterized by distinct phonological and lexical features.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eae611f88190955fbebe2b01835b completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3dd2ff66c8190a0e688e4f9baa5b4 completed March 1, 2026, 6:31 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.