Triple

T3577045
Position Surface form Disambiguated ID Type / Status
Subject Simbirsk, Russian Empire E75712 entity
Predicate laterRenamed P3432 FINISHED
Object Ulyanovsk E398677 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: Ulyanovsk | Statement: [Simbirsk, Russian Empire, laterRenamed, Ulyanovsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ulyanovsk
Context triple: [Simbirsk, Russian Empire, laterRenamed, Ulyanovsk]
  • A. Ulyanovsk chosen
    Ulyanovsk is a city in western Russia on the Volga River, best known as the birthplace of Vladimir Lenin and an important regional industrial and cultural center.
  • B. Ulyanov
    Ulyanov is the Russian surname of Vladimir Lenin, the revolutionary leader and founder of the Soviet state.
  • C. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • D. Saratov
    Saratov is a major city in southwestern Russia known as an important cultural, educational, and industrial center on the banks of the Volga River.
  • E. Penza
    Penza is a city in western Russia known as a regional cultural and industrial center.
  • 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_69ad85d5e3008190bdfe0bacdd1f5a1b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0dba238819083a1d09005c312b8 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf70bb52008190aaf547dff5f0d904 completed March 22, 2026, 4:31 a.m.
Created at: March 8, 2026, 3:21 p.m.