Triple

T20810632
Position Surface form Disambiguated ID Type / Status
Subject Yukhnov E512286 entity
Predicate roadConnection P385 FINISHED
Object Kaluga 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: Kaluga | Statement: [Yukhnov, roadConnection, Kaluga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaluga
Context triple: [Yukhnov, roadConnection, Kaluga]
  • A. Kaluga chosen
    Kaluga is a historic city in western Russia known as a regional administrative center and an important site in several Russian uprisings and military campaigns.
  • B. Koporye
    Koporye is a historic village in Leningrad Oblast, Russia, best known for its medieval fortress and strategic location near the Gulf of Finland.
  • C. Michurinsk
    Michurinsk is a Russian city known as a major center of agricultural science and fruit cultivation, located in Tambov Oblast.
  • D. Kirov
    Kirov is a city in western Russia on the Vyatka River, known as a regional industrial and cultural center with historical roots dating back to the 12th century.
  • E. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • 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_69e0b4cd25088190b48ca9700cd24efc completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2d27a4881908b34679385d8b94b completed April 21, 2026, 12:20 a.m.
Created at: April 16, 2026, 12:40 p.m.