Triple

T15073626
Position Surface form Disambiguated ID Type / Status
Subject Gärdet E379941 entity
Predicate near P350 FINISHED
Object Karlaplan E379938 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: Karlaplan | Statement: [Gärdet, near, Karlaplan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karlaplan
Context triple: [Gärdet, near, Karlaplan]
  • A. Karlaplan chosen
    Karlaplan is a prominent circular plaza and park with a central fountain in the Östermalm district of Stockholm, Sweden.
  • B. Lanke
    Lanke is a village and district within the municipality of Wandlitz in the state of Brandenburg, Germany.
  • C. Kluuvi
    Kluuvi is a central district of Helsinki, Finland, known as the city’s main commercial and business hub.
  • D. Karesi
    Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
  • E. Krempna
    Krempna is a small village in southeastern Poland that serves as a gateway and service center for visitors to Magura National Park in the Low Beskid Mountains.
  • 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_69d85cd7683881908d405c1b5d7b4f7f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dff7fa0570819088a97b28173154cd completed April 15, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fea5cff69c8190b6252509c1aa7ebb completed May 9, 2026, 3:11 a.m.
Created at: April 10, 2026, 3:02 a.m.