Triple

T14941412
Position Surface form Disambiguated ID Type / Status
Subject Roshen Lipetsk Confectionery Factory E372538 entity
Predicate locatedIn P40 FINISHED
Object Lipetsk E903510 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: Lipetsk | Statement: [Roshen Lipetsk Confectionery Factory, locatedIn, Lipetsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lipetsk
Context triple: [Roshen Lipetsk Confectionery Factory, locatedIn, Lipetsk]
  • A. Lipetsk chosen
    Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
  • B. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • C. Izhevsk
    Izhevsk is a major industrial city in western Russia, best known as a center of arms manufacturing and the capital of the Udmurt Republic.
  • D. Tambov
    Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded64a2f24819099b21566756668a2 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c405ecc81909722377a22db84a5 completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 2:38 a.m.