Triple

T10171636
Position Surface form Disambiguated ID Type / Status
Subject Sorpedamm E235343 entity
Predicate locatedInState P40 FINISHED
Object Nordrhein-Westfalen E20221 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: Nordrhein-Westfalen | Statement: [Sorpedamm, locatedInState, Nordrhein-Westfalen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordrhein-Westfalen
Context triple: [Sorpedamm, locatedInState, Nordrhein-Westfalen]
  • A. North Rhine-Westphalia chosen
    North Rhine-Westphalia is Germany’s most populous federal state, known for its major industrial regions, cultural hubs like Cologne and Düsseldorf, and numerous universities and research institutions.
  • B. Rhineland-Palatinate
    Rhineland-Palatinate is a federal state in western Germany known for its wine-growing regions along the Rhine and Moselle rivers and its historic cities such as Mainz and Trier.
  • C. South Westphalia
    South Westphalia is a region in western Germany known for its mixed industrial and rural character, encompassing parts of North Rhine-Westphalia including the Arnsberg area.
  • D. NRW
    NRW is the three-letter National Rail station code used to identify Norwich railway station in the UK rail network.
  • E. Baden-Württemberg
    Baden-Württemberg is a federal state in southwest Germany known for its strong economy, automotive industry, and cities like Stuttgart, Heidelberg, and Freiburg.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec9e4e0c819097dceb7bf7757948 completed April 2, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d65296ee98819096de701e3b945001 completed April 8, 2026, 1:05 p.m.
Created at: March 30, 2026, 9:10 p.m.