Triple

T15333688
Position Surface form Disambiguated ID Type / Status
Subject Hordaland E366605 entity
Predicate containsTown P847 FINISHED
Object Rosendal E1152600 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: Rosendal | Statement: [Hordaland, containsTown, Rosendal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosendal
Context triple: [Hordaland, containsTown, Rosendal]
  • A. Rosendal chosen
    Rosendal is a village in western Norway known for its scenic fjord landscape and the historic Barony Rosendal manor.
  • B. Ottosdal
    Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
  • C. Gröndal
    Gröndal is a residential district in southern Stockholm, Sweden, known for its waterfront location on Lake Mälaren and mix of early 20th-century and modern architecture.
  • D. Kragerø
    Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
  • E. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e0268608190947a58f559a67717 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d3cf84c8190a4655803b12c9721 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 3:17 a.m.