Triple

T9589847
Position Surface form Disambiguated ID Type / Status
Subject Demchugdongrub E231387 entity
Predicate regionOfActivity P82 FINISHED
Object Chahar E360252 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: Chahar | Statement: [Demchugdongrub, regionOfActivity, Chahar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chahar
Context triple: [Demchugdongrub, regionOfActivity, Chahar]
  • A. Chahar chosen
    Chahar was a historical province and region in northern China, bordering Inner Mongolia, that became a key area of Japanese military expansion and control during the Second Sino-Japanese War.
  • B. Chahardangeh
    Chahardangeh is a city in Iran’s Tehran province, serving as one of the urban centers within Islamshahr County.
  • C. Miyāneh
    Miyāneh is a city in East Azerbaijan Province in northwestern Iran, known as a regional agricultural and transportation hub.
  • D. Sorkheh
    Sorkheh is a small city in north-central Iran known for its location within Semnan Province and its semi-arid climate.
  • E. Khar
    Khar is a suburban neighborhood in Mumbai, India, known for its residential areas, shopping streets, and proximity to the Arabian Sea.
  • 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_69ca8482884481908eccdfdf64d6fbf7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99f32e688190bb13bccfa5031f16 completed April 1, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1791e330881908a6ad31a5bdbccec completed April 4, 2026, 8:48 p.m.
Created at: March 30, 2026, 8:06 p.m.