Triple

T14897399
Position Surface form Disambiguated ID Type / Status
Subject Nikolai Yudenich E359913 entity
Predicate familyName P18 FINISHED
Object Yudenich E359913 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: Yudenich | Statement: [Nikolai Yudenich, familyName, Yudenich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yudenich
Context triple: [Nikolai Yudenich, familyName, Yudenich]
  • A. Yudenich chosen
    Yudenich is a Russian surname most notably associated with General Nikolai Yudenich, a leading White movement commander during the Russian Civil War.
  • B. Zaraysk
    Zaraysk is a historic town in Moscow Oblast, Russia, known for its well-preserved medieval kremlin and role as a former regional administrative center.
  • C. Kozelsk
    Kozelsk is a historic town in western Russia known for its medieval defenses and location within Kaluga Oblast.
  • D. Nikolaev
    Nikolaev is the Russian-language name for Mykolaiv, a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
  • E. Suvorovo
    Suvorovo is a small town in northeastern Bulgaria that serves as an administrative and local economic center within Varna Province.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded6084574819098033a9723f3e1c4 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b6966e88190a0ed475b22a77cf1 completed May 8, 2026, 11:02 p.m.
Created at: April 10, 2026, 2:11 a.m.