Triple

T12226264
Position Surface form Disambiguated ID Type / Status
Subject Schmalkaldic League E291358 entity
Predicate hasMember P10 FINISHED
Object City of Erfurt E281989 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: City of Erfurt | Statement: [Schmalkaldic League, hasMember, City of Erfurt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Erfurt
Context triple: [Schmalkaldic League, hasMember, City of Erfurt]
  • A. Erfurt chosen
    Erfurt is a historic German city in the state of Thuringia, known for its well-preserved medieval old town and as an important cultural and educational center.
  • 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. Altdorf bei Nürnberg
    Altdorf bei Nürnberg is a small historic town in Bavaria, Germany, known for its former university and proximity to the city of Nuremberg.
  • D. Karlstadt am Main
    Karlstadt am Main is a historic town in northern Bavaria, Germany, situated on the River Main and known for its medieval old town and surrounding wine-growing region.
  • E. Riedenburg
    Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ca2101c8190955c36704935036a completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a8e6ba081908428ce11196815cc completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:51 p.m.