Triple

T10708142
Position Surface form Disambiguated ID Type / Status
Subject Fritz ter Meer E252461 entity
Predicate placeOfBirth P1 FINISHED
Object Uerdingen E268210 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: Uerdingen | Statement: [Fritz ter Meer, placeOfBirth, Uerdingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uerdingen
Context triple: [Fritz ter Meer, placeOfBirth, Uerdingen]
  • A. Uerdingen chosen
    Uerdingen is a district of the German city of Krefeld, known historically for its chemical industry and location along the Rhine River.
  • B. Weikersheim
    Weikersheim is a small historic town in the Tauber Valley of Baden-Württemberg, Germany, known for its Renaissance castle and well-preserved old town.
  • C. Badenweiler
    Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
  • D. Dornheim
    Dornheim is a small village in Thuringia, Germany, historically noted as the place where Johann Sebastian Bach married Maria Barbara Bach.
  • E. Bruchsal
    Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fde080d48190830eaa863aad61ff completed April 9, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6035cf86081909603cec9aa5bd9d6 completed April 20, 2026, 10:43 a.m.
Created at: April 8, 2026, 9:13 p.m.