Triple

T710651
Position Surface form Disambiguated ID Type / Status
Subject Gelderland E14197 entity
Predicate containsCity P294 FINISHED
Object Arnhem E12070 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: Arnhem | Statement: [Gelderland, containsCity, Arnhem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arnhem
Context triple: [Gelderland, containsCity, Arnhem]
  • A. Arnhem chosen
    Arnhem is a city in the eastern Netherlands best known as the site of a major World War II battle during Operation Market Garden.
  • B. Leeuwarden
    Leeuwarden is a historic city in the northern Netherlands, known as the capital of the province of Friesland and for its rich cultural and architectural heritage.
  • C. Nijmegen
    Nijmegen is a historic Dutch city near the German border that played a crucial strategic role during World War II, particularly in the Allied advance in 1944.
  • D. Hoek van Holland
    Hoek van Holland is a coastal town in the Netherlands known for its North Sea beaches and its strategic location at the mouth of the New Waterway shipping canal.
  • E. Middelburg
    Middelburg is a historic Dutch city in the province of Zeeland that served as an important maritime and trading center during the era of the Dutch East India Company.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a55c99fc8190941c5fd18551792a completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbac916188190b850b247232887a2 completed March 7, 2026, 11:54 p.m.
Created at: March 1, 2026, 7:36 p.m.