Triple

T5193581
Position Surface form Disambiguated ID Type / Status
Subject Stuttgart S-Bahn E117213 entity
Predicate hasStation P35 FINISHED
Object Böblingen E389273 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: Böblingen | Statement: [Stuttgart S-Bahn, hasStation, Böblingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Böblingen
Context triple: [Stuttgart S-Bahn, hasStation, Böblingen]
  • A. Böblingen chosen
    Böblingen is a town in the German state of Baden-Württemberg, near Stuttgart, known for its automotive and technology industries and its role as a regional economic center.
  • B. Esslingen am Neckar
    Esslingen am Neckar is a historic German town near Stuttgart, renowned for its well-preserved medieval old town, half-timbered houses, and hillside vineyards along the Neckar River.
  • C. Bietigheim-Bissingen
    Bietigheim-Bissingen is a town in the German state of Baden-Württemberg known for its historic old town, wine-growing tradition, and location near Stuttgart.
  • D. Baiersbronn
    Baiersbronn is a municipality in Germany’s Black Forest renowned for its scenic landscapes and high concentration of Michelin-starred restaurants.
  • E. 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.
  • 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_69bd4462ed04819084fcb01eb9d2fa74 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79f142488190bc6c57b8ff7ef894 completed March 20, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6536fc20c81909b6c57d559880877 completed March 27, 2026, 9:52 a.m.
Created at: March 20, 2026, 1:46 p.m.