Triple

T622846
Position Surface form Disambiguated ID Type / Status
Subject Stockholm E14550 entity
Predicate hasPart P35 FINISHED
Object Gamla stan E60641 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: Gamla stan | Statement: [Stockholm, hasPart, Gamla stan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gamla stan
Context triple: [Stockholm, hasPart, Gamla stan]
  • A. Old Town, Stockholm chosen
    Old Town, Stockholm is the historic medieval center of Sweden’s capital, known for its cobblestone streets, colorful buildings, and major institutions like the Swedish Academy and the Royal Palace.
  • B. Uppsala
    Uppsala is a historic Swedish city north of Stockholm, known for its prestigious university, medieval cathedral, and role as a cultural and ecclesiastical center.
  • C. Stockholm
    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.
  • D. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • E. Östersund
    Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e402d9c8190936896e3ebb6edc5 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a563cab73c819082b51d64d249143b completed March 2, 2026, 10:17 a.m.
Created at: March 1, 2026, 7:35 p.m.