Triple

T892737
Position Surface form Disambiguated ID Type / Status
Subject Raisa Gorbacheva E19275 entity
Predicate residence P75 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: [Raisa Gorbacheva, residence, Moscow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moscow
Context triple: [Raisa Gorbacheva, residence, Moscow]
  • A. Moscow chosen
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • B. Novosibirsk
    Novosibirsk is a major city in southwestern Siberia and the third-largest city in Russia, known as an important industrial, scientific, and cultural center.
  • C. Yekaterinburg
    Yekaterinburg is a major industrial and cultural city in Russia’s Ural region, historically known as the site of the execution of the last Russian tsar, Nicholas II, and his family.
  • D. 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.
  • E. 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.
  • 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_69a4ad0304b081908d4c92bb2beadb81 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7edf404008190bde0280a67c12b5a completed March 4, 2026, 8:31 a.m.
Created at: March 1, 2026, 7:39 p.m.