Triple

T1946346
Position Surface form Disambiguated ID Type / Status
Subject Turkic world E42061 entity
Predicate hasConceptualCenter P19218 FINISHED
Object Ashgabat E78716 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: Ashgabat | Statement: [Turkic world, hasConceptualCenter, Ashgabat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashgabat
Context triple: [Turkic world, hasConceptualCenter, Ashgabat]
  • A. Ashgabat chosen
    Ashgabat is the largest city and political, economic, and cultural center of Turkmenistan, known for its grand marble architecture and monumental cityscape.
  • B. Baku
    Baku is the capital and largest city of Azerbaijan, known for its rich blend of Islamic heritage and modern architecture on the shores of the Caspian Sea.
  • C. Bishkek
    Bishkek is the largest city and political, economic, and cultural center of Kyrgyzstan, located in the north of the country near the Kyrgyz Ala-Too mountain range.
  • D. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • E. 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.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb7c51c2881908054760c624dd577 completed March 7, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0ac7cd1881908d9284370de529ce completed March 8, 2026, 11:48 p.m.
Created at: March 4, 2026, 7:36 p.m.