Triple

T17364367
Position Surface form Disambiguated ID Type / Status
Subject Talysh region E422148 entity
Predicate hasMajorTown P316 FINISHED
Object Lerik 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: Lerik | Statement: [Talysh region, hasMajorTown, Lerik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lerik
Context triple: [Talysh region, hasMajorTown, Lerik]
  • A. Lerik
    Lerik is a small mountainous city in southern Azerbaijan, known for its lush forests, cool climate, and reputation for residents with exceptional longevity.
  • B. Lerik District chosen
    Lerik District is a mountainous administrative region in southern Azerbaijan known for its lush forests, long-living residents, and location near the Iranian border.
  • C. Sandvika
    Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
  • D. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • E. Trosa
    Trosa is a small coastal town in Södermanland County, Sweden, known for its picturesque wooden houses, harbor, and tourism.
  • 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a4f52988190847230e119a35b87 completed April 19, 2026, 2:13 a.m.
Created at: April 10, 2026, 5:44 a.m.