Triple

T955175
Position Surface form Disambiguated ID Type / Status
Subject Radio Free Europe/Radio Liberty E20608 entity
Predicate hasOfficeIn P1268 FINISHED
Object Dushanbe E98543 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: Dushanbe | Statement: [Radio Free Europe/Radio Liberty, hasOfficeIn, Dushanbe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dushanbe
Context triple: [Radio Free Europe/Radio Liberty, hasOfficeIn, Dushanbe]
  • A. Dushanbe chosen
    Dushanbe is the largest city and political, economic, and cultural center of Tajikistan.
  • 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. 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. Ashgabat
    Ashgabat is the largest city and political, economic, and cultural center of Turkmenistan, known for its grand marble architecture and monumental cityscape.
  • E. Bukhara, Uzbekistan
    Bukhara, Uzbekistan is an ancient Silk Road city renowned for its well-preserved Islamic architecture and historic center, a UNESCO World Heritage Site.
  • 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3f7a7608190b8a8dd2486654bec completed March 1, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a933b00a58819084164f3dd3ecb070 completed March 5, 2026, 7:41 a.m.
Created at: March 1, 2026, 7:40 p.m.