Triple

T889846
Position Surface form Disambiguated ID Type / Status
Subject Sakha Republic E19214 entity
Predicate containsCity P294 FINISHED
Object Lensk E110731 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: Lensk | Statement: [Sakha Republic, containsCity, Lensk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lensk
Context triple: [Sakha Republic, containsCity, Lensk]
  • A. Lensk chosen
    Lensk is a small industrial town in the Sakha Republic of Russia, known for its role in regional river transport and nearby diamond mining activities.
  • B. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • C. Ulyanov
    Ulyanov is the Russian surname of Vladimir Lenin, the revolutionary leader and founder of the Soviet state.
  • D. Komsomolskaya
    Komsomolskaya is one of Moscow Metro’s most famous and ornate stations, renowned for its grand Baroque-style decor and elaborate mosaics.
  • E. Kazan
    Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad0086a081908c47c285896a1f3c completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbad10ae48190af7dcaa8dfff30ec completed March 7, 2026, 11:54 p.m.
Created at: March 1, 2026, 7:39 p.m.