Triple

T16339939
Position Surface form Disambiguated ID Type / Status
Subject Johann Wilhelm Ludwig Gleim E396769 entity
Predicate workLocation P7 FINISHED
Object Halberstadt NE ONNED1

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: Halberstadt | Statement: [Johann Wilhelm Ludwig Gleim, workLocation, Halberstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halberstadt
Context triple: [Johann Wilhelm Ludwig Gleim, workLocation, Halberstadt]
  • A. Halberstadt chosen
    Halberstadt is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and role as a former episcopal seat.
  • B. 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.
  • C. Hildesheim
    Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
  • D. Helmstedt
    Helmstedt is a historic town in Lower Saxony, Germany, known for its medieval architecture and former university.
  • 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 (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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2da09dcf48190b6fdd14b1812c56a completed April 18, 2026, 1:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01953eaa6c819091f7d63a1e3e7070 in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:07 a.m.