Triple

T4286729
Position Surface form Disambiguated ID Type / Status
Subject Taunus E97286 entity
Predicate containsTown P847 FINISHED
Object Weilburg E145657 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: Weilburg | Statement: [Taunus, containsTown, Weilburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weilburg
Context triple: [Taunus, containsTown, Weilburg]
  • A. Weilburg chosen
    Weilburg is a historic town in the German state of Hesse, known for its Renaissance castle and as the ancestral seat of the House of Nassau-Weilburg.
  • B. Wetzlar
    Wetzlar is a historic German city in the state of Hesse, known for its medieval old town and its long tradition in optics and precision engineering.
  • C. Langenau
    Langenau is a small town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its historic center and proximity to the Swabian Jura.
  • D. Nassau-Weilburg
    Nassau-Weilburg was a historical German county and later principality within the Holy Roman Empire, ruled by a branch of the House of Nassau.
  • E. Uerdingen
    Uerdingen is a district of the German city of Krefeld, known historically for its chemical industry and location along the Rhine River.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3505d23d88190a638f2cc2acee9ee completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd36a7c9c81908f325bc8a53db0c8 completed March 20, 2026, 11:08 p.m.
Created at: March 12, 2026, 11:08 p.m.