Triple

T2606923
Position Surface form Disambiguated ID Type / Status
Subject Wartburg Castle E58680 entity
Predicate city P40 FINISHED
Object Eisenach E153084 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: Eisenach | Statement: [Wartburg Castle, city, Eisenach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eisenach
Context triple: [Wartburg Castle, city, Eisenach]
  • A. Eisenach chosen
    Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
  • B. Kronach
    Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
  • C. Gotha
    Gotha is a historic German city in Thuringia known for its former ducal court, cultural heritage, and role as a residence of various German noble houses.
  • D. Mühlhausen
    Mühlhausen is a historic town in central Germany, known for its well-preserved medieval architecture and cultural heritage.
  • E. Schmalkalden
    Schmalkalden is a historic town in the German state of Thuringia, known for its well-preserved medieval architecture and role in Reformation-era politics.
  • 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_69ab4ac3523881909679750c9f8c2dec completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd865c9908190be7e1b572a43972f completed March 7, 2026, 7:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69b56b217af0819084d8aed695b8377b completed March 14, 2026, 2:05 p.m.
Created at: March 6, 2026, 9:49 p.m.