Triple

T20229474
Position Surface form Disambiguated ID Type / Status
Subject Orikhiv sector E495476 entity
Predicate near P350 FINISHED
Object Robotyne area NE NERFINISHED

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: Robotyne area | Statement: [Orikhiv sector, near, Robotyne area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robotyne area
Context triple: [Orikhiv sector, near, Robotyne area]
  • A. Robotyne area chosen
    The Robotyne area is a war-torn sector in southern Ukraine that has become a focal point of intense fighting and strategic military operations in the Russo-Ukrainian War.
  • B. Trongate area
    The Trongate area is a historic district at the eastern end of Glasgow’s city centre, known for its traditional streetscape, shops, bars, and cultural venues.
  • C. Keage Station area
    The Keage Station area is a district in Kyoto, Japan, known as a convenient gateway to nearby cultural and scenic spots such as temples, canals, and walking paths.
  • D. Botlek area
    The Botlek area is an industrial and port district within the Port of Rotterdam, known for its large petrochemical complexes and heavy maritime logistics activities.
  • E. Sidelhorn area
    The Sidelhorn area is a mountainous region in the central Swiss Alps known for its high-altitude terrain and alpine landscapes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66fdc2590819089a946d16c6c0e59 completed April 20, 2026, 6:26 p.m.
Created at: April 11, 2026, 11:39 p.m.