Triple

T151601
Position Surface form Disambiguated ID Type / Status
Subject Moscow Time E3442 entity
Predicate usedIn P98 FINISHED
Object Moscow E1747 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: Moscow | Statement: [Moscow Time, usedIn, Moscow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moscow
Context triple: [Moscow Time, usedIn, Moscow]
  • A. Moscow chosen
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • B. Volgograd
    Volgograd is a major city in southwestern Russia on the Volga River, historically known as Stalingrad and renowned as the site of one of World War II’s most pivotal and brutal battles.
  • C. Sofia
    Sofia is the capital and largest city of Bulgaria, known as a major cultural, economic, and historical center in the Balkans.
  • D. Grozny
    Grozny is the capital and largest city of the Chechen Republic in southwestern Russia, known for its turbulent recent history and extensive post-war reconstruction.
  • E. St. Petersburg
    St. Petersburg is a major Russian port city on the Baltic Sea, renowned for its imperial architecture, cultural heritage, and role as a historic capital of Russia.
  • 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_69a252868de4819080e21c9938bfe8b6 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a2580f55a88190b37b54ee0ed5ac7c completed Feb. 28, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69a36ceb0244819092fdbbd095804b83 completed Feb. 28, 2026, 10:32 p.m.
Created at: Feb. 28, 2026, 2:31 a.m.