Triple

T18500938
Position Surface form Disambiguated ID Type / Status
Subject Emmental E452062 entity
Predicate containsSettlement P847 FINISHED
Object Langenthal 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: Langenthal | Statement: [Emmental, containsSettlement, Langenthal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Langenthal
Context triple: [Emmental, containsSettlement, Langenthal]
  • A. Langenthal chosen
    Langenthal is a town in the canton of Bern in Switzerland, known as a regional economic and transportation hub in the Bernese Mittelland.
  • B. Scheyern
    Scheyern is a Bavarian municipality best known as the site of Scheyern Abbey, a historic Benedictine monastery and ancestral seat of the Wittelsbach family.
  • C. Leitzach
    Leitzach is a river in Bavaria, Germany, known as a tributary of the Mangfall that flows through the Alpine foothills.
  • D. Feldstetten
    Feldstetten is a village in the Swabian Alb region of Baden-Württemberg, Germany, that forms part of the town of Laichingen.
  • E. Nassfeld
    Nassfeld is a major ski and alpine resort area in the Austrian Alps, known for its extensive slopes and modern winter sports facilities.
  • 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_69d8d3855d50819097fc8561b0299dd9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e532c43de48190b49b87c1bb591016 completed April 19, 2026, 7:53 p.m.
Created at: April 10, 2026, 11:36 a.m.