Triple

T10428166
Position Surface form Disambiguated ID Type / Status
Subject Lier E245839 entity
Predicate hasSettlement P1068 FINISHED
Object Lierbyen E862665 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: Lierbyen | Statement: [Lier, hasSettlement, Lierbyen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lierbyen
Context triple: [Lier, hasSettlement, Lierbyen]
  • A. Lierbyen chosen
    Lierbyen is a village in Buskerud county, Norway, serving as the main local hub for commerce and public services in the municipality of Lier.
  • B. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • C. Birkelunden
    Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
  • D. Lemvig
    Lemvig is a small coastal town in western Denmark known for its harbor, hilly landscape, and location along the Limfjord.
  • E. Randaberg
    Randaberg is a coastal municipality in Rogaland county, Norway, situated just north of the city of Stavanger and known for its agriculture and scenic shoreline.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4a7dcc81909a830e08656a1c0c completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87ea554888190bf2ef31e33c0ff14 completed April 10, 2026, 4:37 a.m.
Created at: April 6, 2026, 12:13 p.m.