Triple

T15801204
Position Surface form Disambiguated ID Type / Status
Subject Māturīdism E383101 entity
Predicate originatedIn P410 FINISHED
Object Samarqand E66141 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: Samarqand | Statement: [Māturīdism, originatedIn, Samarqand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samarqand
Context triple: [Māturīdism, originatedIn, Samarqand]
  • A. Samarkand chosen
    Samarkand is an ancient Silk Road city in present-day Uzbekistan renowned for its Timurid-era Islamic architecture and role as a major cultural and commercial center of Central Asia.
  • B. Tashkent
    Tashkent is the capital and largest city of Uzbekistan, a major cultural and economic hub in Central Asia with deep historical ties to the Islamic world.
  • C. Taşkent
    Taşkent is a small mountainous district and town in Turkey’s Konya Province, known for its rural character and scenic Anatolian landscape.
  • D. Andijan
    Andijan is a historic city in eastern Uzbekistan, known as a major cultural and economic center of the Fergana Valley and as the birthplace of the Mughal emperor Babur.
  • E. Urgench
    Urgench is a city in western Uzbekistan that serves as the administrative center of Khorezm Region and a gateway to the historic city of Khiva.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b522a2988190b2a2bde2da31b21e completed April 16, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00606823cc81908c461ef8764ebf41 completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 4:48 a.m.