Triple

T20671070
Position Surface form Disambiguated ID Type / Status
Subject North Caucasus Railway network E508023 entity
Predicate connectsCity P4245 FINISHED
Object Pyatigorsk NE NERFINISHED

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: Pyatigorsk | Statement: [North Caucasus Railway network, connectsCity, Pyatigorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pyatigorsk
Context triple: [North Caucasus Railway network, connectsCity, Pyatigorsk]
  • A. Pyatigorsk chosen
    Pyatigorsk is a historic spa and resort city in southern Russia, known for its mineral springs and location in the North Caucasus region.
  • B. Kislovodsk
    Kislovodsk is a Russian spa and resort city in the North Caucasus, renowned for its mineral springs and mountainous surroundings.
  • C. Tskaltubo
    Tskaltubo is a spa town in western Georgia renowned for its radon-carbonate mineral springs and Soviet-era sanatoriums.
  • D. Gudermes
    Gudermes is a town in the Chechen Republic of Russia that serves as an important regional transport and administrative center.
  • E. Nevrokop
    Nevrokop is the former name of the Bulgarian town now known as Gotse Delchev, located in the southwestern part of Bulgaria.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c1164881909a3bf1e3ddb2bc32 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b5c92aa8819096fbe0ca5101d01b completed April 20, 2026, 11:24 p.m.
Created at: April 16, 2026, 11:44 a.m.