Triple

T21307530
Position Surface form Disambiguated ID Type / Status
Subject Johann Gerhard E525238 entity
Predicate birthPlace P1 FINISHED
Object Quedlinburg 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: Quedlinburg | Statement: [Johann Gerhard, birthPlace, Quedlinburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quedlinburg
Context triple: [Johann Gerhard, birthPlace, Quedlinburg]
  • A. Quedlinburg chosen
    Quedlinburg is a historic German town on the northern edge of the Harz mountains, renowned for its well-preserved medieval architecture and UNESCO World Heritage–listed old town.
  • B. Halberstadt
    Halberstadt is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and role as a former episcopal seat.
  • C. Wolfenbüttel
    Wolfenbüttel is a historic town in Lower Saxony, Germany, known for its Renaissance castle and rich cultural heritage.
  • D. Malching
    Malching is a small municipality in southeastern Bavaria, Germany, situated near the Austrian border in the district of Passau.
  • E. Querfurt
    Querfurt is a small historic town in the German state of Saxony-Anhalt, known for its well-preserved medieval castle and old town.
  • 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_69e0b518b8948190ad69cf9a8784d397 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e75aa7b2f08190bea46f0107bcc045 completed April 21, 2026, 11:08 a.m.
Created at: April 16, 2026, 4:05 p.m.