Triple

T2108934
Position Surface form Disambiguated ID Type / Status
Subject Tverskaya Street, Moscow E42458 entity
Predicate near P350 FINISHED
Object Red Square E18230 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: Red Square | Statement: [Tverskaya Street, Moscow, near, Red Square]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red Square
Context triple: [Tverskaya Street, Moscow, near, Red Square]
  • A. Red Square chosen
    Red Square is Moscow’s most famous historic plaza, known as a symbolic center of Russia and a UNESCO World Heritage site surrounded by landmarks like the Kremlin and Saint Basil’s Cathedral.
  • B. Lubyanka Square, Moscow
    Lubyanka Square, Moscow is a central Moscow square historically known as the site of Russia’s main security service headquarters and the former KGB prison.
  • C. Theatre Square, Moscow
    Theatre Square in Moscow is a historic central square renowned as a cultural hub, surrounded by landmark institutions including the Bolshoi Theatre.
  • D. Vosstaniya Square
    Vosstaniya Square is a major public square and transport hub in central Saint Petersburg, Russia, known for its proximity to Moskovsky railway station and busy Nevsky Prospekt.
  • E. Sennaya Square
    Sennaya Square is a historic public square in central Saint Petersburg, Russia, long known as a bustling commercial hub and a setting in several of Dostoevsky’s works.
  • 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_69a8871040f08190aac2e2d0ab6b47ad completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbae03f308190841f5a419bb821f6 completed March 7, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d8bffd0819095629956f9584222 completed March 9, 2026, 5:41 a.m.
Created at: March 4, 2026, 7:43 p.m.