Triple

T161182
Position Surface form Disambiguated ID Type / Status
Subject Russian election protests 2011 E3288 entity
Predicate location P40 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: [Russian election protests 2011, location, Moscow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moscow
Context triple: [Russian election protests 2011, location, Moscow]
  • A. Moscow chosen
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • B. 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.
  • C. Nizhny Novgorod
    Nizhny Novgorod is a major Russian city located at the confluence of the Volga and Oka rivers, known for its historic Kremlin, industrial significance, and role as a key cultural and economic center in the Volga region.
  • D. Rostov-on-Don
    Rostov-on-Don is a major port city in southern Russia, located on the Don River near the Sea of Azov and serving as an important administrative, cultural, and industrial center of the region.
  • E. Sochi
    Sochi is a Russian resort city on the Black Sea coast, known for its subtropical climate, beaches, and as the host of the 2014 Winter Olympics.
  • 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_69a2527757ec819090b8becb2cf1a862 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a25856d934819095460b2ea566eb6b completed Feb. 28, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69a39d0168508190b6f6766a75dd0e34 completed March 1, 2026, 1:57 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.