Triple

T9703697
Position Surface form Disambiguated ID Type / Status
Subject Mór E234841 entity
Predicate locatedBetween P1262 FINISHED
Object Bakony Hills E488178 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: Bakony Hills | Statement: [Mór, locatedBetween, Bakony Hills]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bakony Hills
Context triple: [Mór, locatedBetween, Bakony Hills]
  • A. Bakony Mountains chosen
    The Bakony Mountains are a forested mountain range in western Hungary, forming part of the Transdanubian Mountains and known for their karst landscapes, hiking trails, and natural beauty.
  • B. Lővérek Hills
    Lővérek Hills is a forested hilly area near Sopron in western Hungary, known for its hiking trails, lookout towers, and recreational opportunities.
  • C. Zemplén Mountains
    The Zemplén Mountains are a volcanic mountain range in northeastern Hungary and southeastern Slovakia, known for their forested landscapes, castles, and wine-producing regions.
  • D. Börzsöny Mountains
    The Börzsöny Mountains are a volcanic mountain range in northern Hungary known for their forested peaks, rich wildlife, and popular hiking trails.
  • E. Gödöllő Hills
    Gödöllő Hills is a hilly geographical region in central Hungary known for its rolling landscapes, forests, and proximity to Budapest.
  • 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_69ca84cc78808190a56f3402b7c139a7 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d73a0148190ad4178fd462cdd9c completed April 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcc0117c8190bc82a985ce59623d completed April 5, 2026, 1:37 a.m.
Created at: March 30, 2026, 8:18 p.m.