Triple

T22859684
Position Surface form Disambiguated ID Type / Status
Subject Lorze River E566879 entity
Predicate flowsThrough P225 FINISHED
Object Ägerital NE NERFINISHED

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: Ägerital | Statement: [Lorze River, flowsThrough, Ägerital]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ägerital
Context triple: [Lorze River, flowsThrough, Ägerital]
  • A. Ägeri chosen
    Ägeri is a municipality in the canton of Zug in central Switzerland, known for its scenic Ägerisee (Lake Ägeri) and surrounding pre-Alpine landscape.
  • B. Arogno
    Arogno is a small municipality in the canton of Ticino in southern Switzerland, located near Lake Lugano and the Italian border.
  • C. Aigen
    Aigen is a district of Salzburg, Austria, known for its villas, green spaces, and proximity to the Gaisberg mountain.
  • D. Älta
    Älta is a suburban locality in Nacka Municipality near Stockholm, Sweden, known for its residential areas and proximity to lakes and natural recreational areas.
  • E. Angerberg
    Angerberg is a small municipality in the Austrian state of Tyrol, known for its alpine scenery and rural character.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24589083081908d5694c4fdc80086 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17ec082c08190943e6cfc2e25c5cc completed April 29, 2026, 3:45 a.m.
Created at: April 17, 2026, 3:37 p.m.