Triple

T10513108
Position Surface form Disambiguated ID Type / Status
Subject Tain-l’Hermitage E247964 entity
Predicate twinnedWith P1072 FINISHED
Object Biberach an der Riß E381274 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: Biberach an der Riß | Statement: [Tain-l’Hermitage, twinnedWith, Biberach an der Riß]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biberach an der Riß
Context triple: [Tain-l’Hermitage, twinnedWith, Biberach an der Riß]
  • A. Biberach an der Riß chosen
    Biberach an der Riß is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval old town and traditional Swabian culture.
  • B. Miesbach
    Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
  • C. Blaubeuren
    Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
  • D. Bochingen
    Bochingen is a village and district of the town Oberndorf am Neckar in the state of Baden-Württemberg in southwestern Germany.
  • E. Baiersbronn
    Baiersbronn is a municipality in Germany’s Black Forest renowned for its scenic landscapes and high concentration of Michelin-starred restaurants.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509ca214481909b3ed9265e7a6704 completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69dff7628eb081909ab3a445238bb682 completed April 15, 2026, 8:38 p.m.
Created at: April 6, 2026, 12:27 p.m.