Triple

T21002466
Position Surface form Disambiguated ID Type / Status
Subject province of Södermanland E517328 entity
Predicate containsCity P294 FINISHED
Object Katrineholm 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: Katrineholm | Statement: [province of Södermanland, containsCity, Katrineholm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katrineholm
Context triple: [province of Södermanland, containsCity, Katrineholm]
  • A. Katrineholm chosen
    Katrineholm is a small Swedish town known as a regional transport hub and service center in central Södermanland.
  • B. Djursholm
    Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
  • C. Botkyrka
    Botkyrka is a municipality in Stockholm County, Sweden, historically associated with the veneration of Saint Botvid and known for its cultural diversity and suburban communities.
  • D. Dronninglund
    Dronninglund is a town in northern Denmark known for its historic castle and surrounding natural landscapes.
  • E. Rosersberg
    Rosersberg is a locality in Stockholm County, Sweden, known for its historic Rosersberg Palace and its location near Stockholm Arlanda Airport.
  • 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_69e0b50192308190a284fcc89dd23a49 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc38b8688190860fba1b58e1b3e6 completed April 21, 2026, 4:25 a.m.
Created at: April 16, 2026, 1:52 p.m.