Triple

T11913257
Position Surface form Disambiguated ID Type / Status
Subject Lake Seliger E283446 entity
Predicate nearestTown P350 FINISHED
Object Ostashkov E338493 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: Ostashkov | Statement: [Lake Seliger, nearestTown, Ostashkov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ostashkov
Context triple: [Lake Seliger, nearestTown, Ostashkov]
  • A. Ostashkov chosen
    Ostashkov is a historic town in western Russia situated on the shores of Lake Seliger, known as a local tourist and pilgrimage center.
  • B. Yuzovka
    Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • C. Melekhovo
    Melekhovo is a rural locality in Russia known for housing the IK-6 high-security penal colony.
  • D. Kastornoye
    Kastornoye is a locality in Russia historically notable as the namesake and focal area of the Voronezh–Kastornoye military offensive during World War II.
  • E. Bolkhov
    Bolkhov is a historic town in western Russia known for its old churches and traditional architecture within Oryol Oblast.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e528f6748190ac873a040a61fa93 completed April 10, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69f5f63ac68c819090a0361a16e8452d completed May 2, 2026, 1:03 p.m.
Created at: April 8, 2026, 9:44 p.m.