Triple

T19564685
Position Surface form Disambiguated ID Type / Status
Subject Kinzigtal E489547 entity
Predicate hasTown P847 FINISHED
Object Wolfach 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: Wolfach | Statement: [Kinzigtal, hasTown, Wolfach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolfach
Context triple: [Kinzigtal, hasTown, Wolfach]
  • A. Wolfach chosen
    Wolfach is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its traditional glassmaking and picturesque setting along the Kinzig River.
  • B. Wuhletal
    Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
  • C. Pfaffenweiler
    Pfaffenweiler is a small municipality in southwestern Germany’s Baden-Württemberg region, situated near Freiburg im Breisgau and known for its winegrowing and picturesque Black Forest surroundings.
  • D. Oppenweiler
    Oppenweiler is a small municipality in the German state of Baden-Württemberg, situated in the Rems-Murr district near the city of Stuttgart.
  • E. Odelzhausen
    Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
  • 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63f76b220819096e668534c6bac67 completed April 20, 2026, 3 p.m.
Created at: April 10, 2026, 1:42 p.m.