Triple

T9803085
Position Surface form Disambiguated ID Type / Status
Subject Bayda E237887 entity
Predicate hasNameInArabic P6450 FINISHED
Object البيضاء E428431 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: البيضاء | Statement: [Bayda, hasNameInArabic, البيضاء]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: البيضاء
Context triple: [Bayda, hasNameInArabic, البيضاء]
  • A. البيضاء chosen
    البيضاء هي مدينة ليبية تقع في الجبل الأخضر بشرق البلاد وتعد من المراكز الإدارية والاقتصادية المهمة هناك.
  • B. La Blanca
    La Blanca is a municipality located in the San Marcos Department of western Guatemala, known for its rural character and agricultural activities.
  • C. Llano Blanco
    Llano Blanco is a small settlement located within the municipality of El Rosario in Mexico.
  • D. Biàncáitiān
    Biàncáitiān is a Chinese Buddhist deity associated with wisdom, learning, and the arts, regarded as the counterpart of the Hindu goddess Saraswati.
  • E. Peñas Blancas
    Peñas Blancas is a border town between Costa Rica and Nicaragua that serves as a major overland crossing point for travelers and freight in Central America.
  • 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_69ca84dd4608819097ff4ed00feca280 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdab78832481909b184b21a8a46e50 completed April 1, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c4538760819099ba1e392d31a135 completed April 5, 2026, 2:09 a.m.
Created at: March 30, 2026, 8:29 p.m.