Triple

T10824141
Position Surface form Disambiguated ID Type / Status
Subject Central Arabia E255450 entity
Predicate contains P35 FINISHED
Object Unaizah E598508 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: Unaizah | Statement: [Central Arabia, contains, Unaizah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unaizah
Context triple: [Central Arabia, contains, Unaizah]
  • A. Unaizah chosen
    Unaizah is a historic oasis city in central Saudi Arabia’s Qassim region, known for its date farms, traditional markets, and cultural heritage.
  • B. Anizah
    Anizah is a prominent Arab tribal confederation historically associated with the Najd region of the Arabian Peninsula.
  • C. Aziza
    Aziza is a traditional deity revered in Urhobo religion, associated with spiritual protection and guidance within the culture of the Urhobo people of Nigeria.
  • D. Najihah
    Najihah is a feminine given name of Malay origin, notably borne by Tuanku Najihah, a former royal consort and Raja Permaisuri Agong of Malaysia.
  • E. Anisa
    Anisa is a feminine given name of Arabic origin commonly used in various Muslim-majority cultures.
  • 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_69d6aa8081448190a9324184f2bd1c26 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d734cf7918819094d36ea208c80d12 completed April 9, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb1096cbc81908f3eda562c2da042 completed April 14, 2026, 9:26 p.m.
Created at: April 8, 2026, 9:19 p.m.