Triple

T13456321
Position Surface form Disambiguated ID Type / Status
Subject Turkmenistan Time E311241 entity
Predicate usedInCapitalCity P20460 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: [Turkmenistan Time, usedInCapitalCity, Ashgabat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashgabat
Context triple: [Turkmenistan Time, usedInCapitalCity, 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. Akçaabat
    Akçaabat is a coastal town and district in Turkey’s Trabzon Province on the Black Sea, known for its historic architecture and distinctive local cuisine.
  • C. Astara
    Astara is a coastal city in northern Iran near the border with Azerbaijan, known as an important trade and transit hub on the Caspian Sea.
  • D. 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.
  • E. 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.
  • 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf0a75008190a508060c85f73604 completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78ad5c68881908264947993bc7811 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:41 p.m.