Triple

T3583067
Position Surface form Disambiguated ID Type / Status
Subject Soviet Western Front E75845 entity
Predicate headquartersLocation P62 FINISHED
Object Vyazma E366953 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: Vyazma | Statement: [Soviet Western Front, headquartersLocation, Vyazma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vyazma
Context triple: [Soviet Western Front, headquartersLocation, Vyazma]
  • A. Vyazma chosen
    Vyazma is a historic town in Smolensk Oblast, western Russia, known for its strategic military significance, particularly during World War II.
  • B. Rzhev
    Rzhev is a historic town in western Russia known for its strategic location on the Volga River and as the site of major World War II battles.
  • C. Babruysk
    Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
  • D. Yudenich
    Yudenich is a Russian surname most notably associated with General Nikolai Yudenich, a leading White movement commander during the Russian Civil War.
  • E. Orsha
    Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
  • 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_69ad85d6dc3c8190b491b79b83e25461 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc104846c81908b6fbde7061464b4 completed March 8, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b43303f1088190be5e4460f579efb8 completed March 13, 2026, 3:53 p.m.
Created at: March 8, 2026, 3:21 p.m.