Triple

T8790678
Position Surface form Disambiguated ID Type / Status
Subject Venyovsky Uyezd E209155 entity
Predicate namedAfter P63 FINISHED
Object Venyov E758935 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: Venyov | Statement: [Venyovsky Uyezd, namedAfter, Venyov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Venyov
Context triple: [Venyovsky Uyezd, namedAfter, Venyov]
  • A. Venyov chosen
    Venyov is a historic town in Tula Oblast, Russia, known for its role as a local administrative and cultural center.
  • B. Vidnoye
    Vidnoye is a small town in Moscow Oblast, Russia, functioning largely as a residential and industrial satellite of Moscow.
  • C. Devnya
    Devnya is an industrial town in northeastern Bulgaria known for its large chemical and cement plants and its location near the Black Sea port city of Varna.
  • D. Sosva
    Sosva is a rural locality in Sverdlovsk Oblast, Russia, historically known as the site of a Soviet-era labor camp where Finnish communist leader Kullervo Manner died.
  • E. Viotá
    Viotá is a rural municipality in the Cundinamarca department of Colombia, known for its coffee production and location in the Andean region southwest of Bogotá.
  • 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_69ca836168108190bb43d3dc235c1f55 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f8d25f881908863d636fa57a8a2 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfa046aabc8190abca2957593edc8b completed April 3, 2026, 11:11 a.m.
Created at: March 30, 2026, 6:43 p.m.