Triple

T1075921
Position Surface form Disambiguated ID Type / Status
Subject Vallentuna Municipality E23837 entity
Predicate hasSettlement P1068 FINISHED
Object Vallentuna E138535 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: Vallentuna | Statement: [Vallentuna Municipality, hasSettlement, Vallentuna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vallentuna
Context triple: [Vallentuna Municipality, hasSettlement, Vallentuna]
  • A. Vallentuna chosen
    Vallentuna is a locality in Stockholm County, Sweden, known as a suburban community within the Stockholm metropolitan area.
  • B. Storvreten
    Storvreten is a residential locality within Botkyrka Municipality in the Stockholm County area of Sweden.
  • C. Vallader
    Vallader is a major dialect of the Romansh language spoken primarily in Switzerland’s Lower Engadine region and used in local literature and education.
  • D. Valbo
    Valbo is a locality in Gävleborg County, Sweden, known as the hometown of NHL ice hockey star Nicklas Bäckström.
  • E. Veltro
    Veltro is the nickname of the Macchi C.205, an Italian World War II fighter aircraft renowned for its speed and agility.
  • 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_69a493f1ddf48190a99d54b00e99f8ce completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b92e480c81909a848b48c196a293 completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8303cbec8190a3b8a9bad2434ee7 completed March 7, 2026, 7:56 p.m.
Created at: March 1, 2026, 7:42 p.m.