Triple

T20206884
Position Surface form Disambiguated ID Type / Status
Subject Lezhë County E493374 entity
Predicate bordersCounty P6346 FINISHED
Object Dibër County 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: Dibër County | Statement: [Lezhë County, bordersCounty, Dibër County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dibër County
Context triple: [Lezhë County, bordersCounty, Dibër County]
  • A. Dibër County chosen
    Dibër County is an administrative region in northeastern Albania known for its mountainous terrain, rural communities, and proximity to the North Macedonian border.
  • B. Landeh County
    Landeh County is an administrative subdivision in southwestern Iran, located within Kohgiluyeh and Boyer-Ahmad Province.
  • C. Luannan County
    Luannan County is an administrative county under the jurisdiction of Tangshan in Hebei Province, northern China, known for its agriculture and proximity to the Bohai Sea.
  • D. Paegam County
    Paegam County is a rural administrative region in northern North Korea known for its mountainous terrain and proximity to the Chinese border.
  • E. McKean County
    McKean County is a largely rural county in north-central Pennsylvania known for its forests, outdoor recreation, and small industrial communities.
  • 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d922ebc8190ae012da8ceba74dd completed April 20, 2026, 6:16 p.m.
Created at: April 11, 2026, 11:38 p.m.