Triple

T15365976
Position Surface form Disambiguated ID Type / Status
Subject Friezland railway station E367414 entity
Predicate served P17148 FINISHED
Object Friezland E367414 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: Friezland | Statement: [Friezland railway station, served, Friezland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friezland
Context triple: [Friezland railway station, served, Friezland]
  • A. Friezland chosen
    Friezland is a small village in the civil parish of Saddleworth, within the Metropolitan Borough of Oldham in Greater Manchester, England.
  • B. Skarfia
    Skarfia is a small settlement in Greece located within the administrative boundaries of the Agia municipality.
  • C. Erblande
    Erblande refers to the core hereditary territories of the Habsburg dynasty in Central Europe, forming the dynastic heartland of their monarchy.
  • D. Krakozhia
    Krakozhia is a fictional Eastern European country featured in the film "The Terminal," serving as the homeland of the main character Viktor Navorski.
  • E. Ostland
    Ostland was a historical region in Eastern Europe that roughly encompassed the Baltic states and parts of western Belarus.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e497de48190be249b110999ec5c completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b4e968c8190a16824ee3ede13b2 completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:18 a.m.