Triple

T12920938
Position Surface form Disambiguated ID Type / Status
Subject NIC.TM E309117 entity
Predicate country P26 FINISHED
Object Turkmenistan E15860 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: Turkmenistan | Statement: [NIC.TM, country, Turkmenistan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turkmenistan
Context triple: [NIC.TM, country, Turkmenistan]
  • A. Turkmenistan chosen
    Turkmenistan is a landlocked Central Asian country rich in natural gas resources, known for its desert landscapes, authoritarian political system, and capital city Ashgabat.
  • B. Tajikistan
    Tajikistan is a landlocked, mountainous country in Central Asia known for its rugged Pamir range and as a former Soviet republic with an economy centered on agriculture, hydropower, and remittances.
  • C. Takestan
    Takestan is a city in northwestern Iran known as an important agricultural and viticultural center within Qazvin Province.
  • D. Uzbekistan
    Uzbekistan is a landlocked Central Asian country known for its Silk Road heritage, including historic cities like Samarkand and Bukhara, and for being a major producer of cotton and natural gas.
  • E. Kyrgyzstan
    Kyrgyzstan is a landlocked Central Asian country known for its mountainous terrain, nomadic heritage, and status as a former Soviet republic.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971e7f6e881908c7bb12283898c80 completed April 10, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8d39d4c81908fab65129f292862 completed May 3, 2026, 2:54 a.m.
Created at: April 9, 2026, 5:41 p.m.