Triple

T7541471
Position Surface form Disambiguated ID Type / Status
Subject Djurgårdens IF E178284 entity
Predicate city P40 FINISHED
Object Stockholm E14550 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: Stockholm | Statement: [Djurgårdens IF, city, Stockholm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stockholm
Context triple: [Djurgårdens IF, city, Stockholm]
  • A. Stockholm chosen
    Stockholm is the capital city of Sweden, renowned for its historic architecture, cultural institutions, and role as a major political, economic, and scientific center in Scandinavia.
  • B. Stockholm
    Stockholm is a fictional character in the Spanish television series "Money Heist" (La Casa de Papel), known for evolving from a hostage to a member of the heist crew.
  • C. Gothenburg
    Gothenburg is a small city in western Nebraska known for its historic Pony Express station and classic Midwestern agricultural community.
  • D. Gothenburg
    Gothenburg is Sweden’s second-largest city, a major port on the country’s west coast known for its maritime heritage, universities, and vibrant cultural scene.
  • E. Stockholm Värtahamnen
    Stockholm Värtahamnen is a major ferry and cargo terminal area in northeastern central Stockholm, serving both domestic and international maritime traffic.
  • 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_69c69f2be3888190a6667a27f8f195e9 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8750f80819088ddfb7a5580b5df completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8614787988190bb5479677f8485d2 completed March 28, 2026, 11:16 p.m.
Created at: March 27, 2026, 3:48 p.m.