Triple

T2182879
Position Surface form Disambiguated ID Type / Status
Subject Thuringia E49084 entity
Predicate containsCity P294 FINISHED
Object Gotha E258439 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: Gotha | Statement: [Thuringia, containsCity, Gotha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gotha
Context triple: [Thuringia, containsCity, Gotha]
  • A. Gotha chosen
    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.
  • B. Eisenach
    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.
  • C. Nordhausen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • D. Jena
    Jena is a historic university city in the German state of Thuringia, known for its role in optics, philosophy, and science.
  • E. Coburg
    Coburg is a historic town in northern Bavaria, Germany, known for its well-preserved medieval architecture and its former role as the seat of the Duchy of Saxe-Coburg and Gotha.
  • 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_69a88aa72d348190a9544bb5b8a4e71d completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbf0d551881909d7f907378e1b2b7 completed March 7, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_69b38b9e52688190bd9dc7fb17e892f8 completed March 13, 2026, 3:59 a.m.
Created at: March 4, 2026, 7:45 p.m.