Triple

T1765925
Position Surface form Disambiguated ID Type / Status
Subject Blaustein E38762 entity
Predicate hasSubdivision P747 FINISHED
Object Herrlingen E30346 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: Herrlingen | Statement: [Blaustein, hasSubdivision, Herrlingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herrlingen
Context triple: [Blaustein, hasSubdivision, Herrlingen]
  • A. Herrlingen chosen
    Herrlingen is a small village in the German state of Baden-Württemberg, historically noted as the place where Field Marshal Erwin Rommel spent his final days during World War II.
  • B. 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.
  • C. Sindelfingen
    Sindelfingen is a city in the German state of Baden-Württemberg known for its major Mercedes-Benz automobile production plant and close ties to the Stuttgart metropolitan area.
  • D. Pforzheim
    Pforzheim is a city in southwestern Germany, historically known for its jewelry and watchmaking industry and its heavy destruction during World War II.
  • E. Schwäbisch Gmünd
    Schwäbisch Gmünd is a historic town in the German state of Baden-Württemberg, known for its medieval architecture and long tradition of metalworking and jewelry craftsmanship.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6467c3f08190abc8a06269ede908 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b4b974081908da05bc63f923215 completed March 9, 2026, 8:19 p.m.
Created at: March 4, 2026, 7:31 p.m.