Triple

T16950088
Position Surface form Disambiguated ID Type / Status
Subject Lazeshchyna E411158 entity
Predicate nearMountainRange P651 FINISHED
Object Chornohora E846395 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: Chornohora | Statement: [Lazeshchyna, nearMountainRange, Chornohora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chornohora
Context triple: [Lazeshchyna, nearMountainRange, Chornohora]
  • A. Chornohora chosen
    Chornohora is a prominent mountain range in the Ukrainian Carpathians, known for containing some of the country’s highest peaks and scenic alpine landscapes.
  • B. Hoverla
    Hoverla is the tallest mountain in Ukraine, located in the Carpathian range and popular for hiking and tourism.
  • C. Konyavska Mountain
    Konyavska Mountain is a small mountain range in western Bulgaria known for its forested slopes and scenic views near the town of Kyustendil.
  • D. Sněžka
    Sněžka is the highest mountain in the Czech Republic, located on the border with Poland in the Krkonoše range.
  • E. Bieszczady Mountains
    The Bieszczady Mountains are a remote, scenic mountain range in southeastern Poland known for their rolling forested hills, wild nature, and popular hiking trails.
  • 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_69d886c9c9d481909afe222093641cae completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cfb570b08190ae3385b0cad32668 completed April 18, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012eccd1e48190aa0dc64562d6ff1f completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:31 a.m.