Triple

T7851114
Position Surface form Disambiguated ID Type / Status
Subject canton of Uri E182054 entity
Predicate hasMunicipalities P747 FINISHED
Object Wassen E425683 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: Wassen | Statement: [canton of Uri, hasMunicipalities, Wassen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wassen
Context triple: [canton of Uri, hasMunicipalities, Wassen]
  • A. Wassen chosen
    Wassen is a small Swiss village in the canton of Uri, known for its picturesque church and location along the Gotthard railway and road routes in the central Alps.
  • B. Nissewaard
    Nissewaard is a municipality and town in the western Netherlands, located on the island of Voorne-Putten in the province of South Holland.
  • C. Woudenberg
    Woudenberg is a small Dutch municipality and town located in the central Netherlands.
  • D. Wassenaar
    Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
  • E. Schwansen
    Schwansen is a rural peninsula in northern Germany situated between the Schlei inlet and the Eckernförde Bay in the state of Schleswig-Holstein.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb18eaac508190bf373b1d50b52e1e completed March 31, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbdf21add88190bc07d3164e940116 completed March 31, 2026, 2:50 p.m.
Created at: March 30, 2026, 4:50 p.m.