Triple

T8343908
Position Surface form Disambiguated ID Type / Status
Subject Semnan Province E195987 entity
Predicate hasDesert P1024 FINISHED
Object Dasht-e Kavir E309821 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: Dasht-e Kavir | Statement: [Semnan Province, hasDesert, Dasht-e Kavir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dasht-e Kavir
Context triple: [Semnan Province, hasDesert, Dasht-e Kavir]
  • A. Dasht-e Kavir chosen
    Dasht-e Kavir is Iran’s vast central salt desert, characterized by arid plains, salt flats, and extreme climatic conditions.
  • B. Karakum Desert
    The Karakum Desert is a vast arid region covering much of Turkmenistan, known for its extreme climate, sparse population, and significant oil and natural gas reserves.
  • C. Tabas Desert
    The Tabas Desert is an arid region in eastern Iran, historically notable as the site of the failed 1980 U.S. military rescue mission Operation Eagle Claw during the Iran hostage crisis.
  • D. Dasht-e Lut
    Dasht-e Lut is a vast desert in southeastern Iran known as one of the hottest and driest places on Earth.
  • E. Taklamakan Desert
    The Taklamakan Desert is a vast, arid sand desert in China’s Xinjiang region, known for its extreme dryness, shifting dunes, and historical role along the Silk Road.
  • 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_69ca82edd63c8190b876b8465464c5fa completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fed6b588190ba5593859c8effc2 completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc733f7848190ab60098cb178dbfc completed April 2, 2026, 1:32 a.m.
Created at: March 30, 2026, 5:58 p.m.