Triple

T9651300
Position Surface form Disambiguated ID Type / Status
Subject Transcaspia E233339 entity
Predicate capital P234 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: [Transcaspia, capital, Ashgabat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashgabat
Context triple: [Transcaspia, capital, 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_69ca848b31648190b57aa55da20285be completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9baf9a1c819098c407ea7d42e6d1 completed April 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18a03438c8190a3419cbed7af4cd4 completed April 4, 2026, 10 p.m.
Created at: March 30, 2026, 8:13 p.m.