Triple

T1917664
Position Surface form Disambiguated ID Type / Status
Subject Asir region E40054 entity
Predicate hasMajorCity P316 FINISHED
Object Abha E214751 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: Abha | Statement: [Asir region, hasMajorCity, Abha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abha
Context triple: [Asir region, hasMajorCity, Abha]
  • A. Abha chosen
    Abha is a city in southwestern Saudi Arabia known for its cool highland climate, mountainous scenery, and role as a cultural and administrative center of the Asir region.
  • B. Amritsar
    Amritsar is a historic city in the Indian state of Punjab, renowned as the spiritual center of Sikhism and home to the Golden Temple.
  • C. Jetpur
    Jetpur is a textile and dyeing hub town in Gujarat, India, known for its cotton saree printing and screen-printing industries.
  • D. Dhar
    Dhar is a historic town and administrative center in the Indian state of Madhya Pradesh, known for its medieval forts, Islamic architecture, and cultural heritage.
  • E. Jaisalmer
    Jaisalmer is a historic city in the Indian state of Rajasthan, famed for its golden sandstone architecture, hilltop fort, and role as a former trading center on desert caravan routes.
  • 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb2107fe48190bafff825f1f805ad completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbae5760819083c046d0941513de completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:35 p.m.