Triple

T1766862
Position Surface form Disambiguated ID Type / Status
Subject Leningrad Oblast E38781 entity
Predicate containsCity P294 FINISHED
Object Volkhov E128726 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: Volkhov | Statement: [Leningrad Oblast, containsCity, Volkhov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volkhov
Context triple: [Leningrad Oblast, containsCity, Volkhov]
  • A. Volkhov chosen
    Volkhov is a town in Leningrad Oblast, Russia, situated along the Volkhov River and known for its hydroelectric power station and industrial significance.
  • B. Volzhsky
    Volzhsky is a major industrial city in southwestern Russia located across the Volga River from Volgograd.
  • C. Vyatskoye
    Vyatskoye is a rural locality in Russia’s Khabarovsk Krai, historically noted as the birthplace of North Korean leader Kim Jong Il.
  • D. Kholmogory
    Kholmogory is a historic Russian town in the Arkhangelsk region that served as an important early northern trading and administrative center.
  • E. Ust-Luga
    Ust-Luga is a major Russian Baltic Sea port town that serves as a key cargo and energy export hub for the Leningrad Oblast region.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa646914048190bbe282a3d4768835 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb98fee88190804f368b484c7305 completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:31 p.m.