Triple

T16350065
Position Surface form Disambiguated ID Type / Status
Subject Diez E397038 entity
Predicate locatedNear P294 FINISHED
Object Limburg an der Lahn E224973 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: Limburg an der Lahn | Statement: [Diez, locatedNear, Limburg an der Lahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limburg an der Lahn
Context triple: [Diez, locatedNear, Limburg an der Lahn]
  • A. Limburg an der Lahn chosen
    Limburg an der Lahn is a historic town in western Hesse, Germany, known for its well-preserved medieval old town and prominent hilltop cathedral overlooking the Lahn River.
  • B. Limburg-Weilburg
    Limburg-Weilburg is a rural district in the German state of Hesse, known for its historic town of Limburg an der Lahn and its location along the Lahn River.
  • C. Limburg
    Limburg is a province in the southeastern Netherlands known for its hilly landscape, distinct Limburgish culture and language, and the city of Maastricht.
  • D. Limburg
    Limburg is a historical region in the Low Countries that was once part of the Habsburg Netherlands and has since been divided mainly between present-day Belgium and the Netherlands.
  • E. Diepholz
    Diepholz is a town in Lower Saxony, Germany, known as a local administrative center and for its surrounding lake district and agricultural landscape.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2da120ec081909bbf32bd128b2e01 completed April 18, 2026, 1:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00355a7fb481908ed33a86c880fd49 completed May 10, 2026, 7:35 a.m.
Created at: April 10, 2026, 5:07 a.m.