Triple

T8017978
Position Surface form Disambiguated ID Type / Status
Subject Bundesstraße 10 E186667 entity
Predicate connectsCity P4245 FINISHED
Object Pforzheim E208654 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: Pforzheim | Statement: [Bundesstraße 10, connectsCity, Pforzheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pforzheim
Context triple: [Bundesstraße 10, connectsCity, Pforzheim]
  • A. Pforzheim chosen
    Pforzheim is a city in southwestern Germany, historically known for its jewelry and watchmaking industry and its heavy destruction during World War II.
  • B. Rastatt
    Rastatt is a historic town in southwestern Germany, known for its Baroque architecture and its role as the site of significant early 18th-century peace negotiations.
  • C. Rottweil
    Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
  • D. Göppingen
    Göppingen is a town in the German state of Baden-Württemberg known as an industrial and administrative center in the Filstal valley near Stuttgart.
  • E. Albstadt
    Albstadt is a town in the Swabian Jura region of Baden-Württemberg, Germany, known for its textile industry, scenic hiking and cycling routes, and role as a regional economic center.
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3df4f1b8819089a8b67f136bce9a completed March 31, 2026, 3:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfaae99194819095cf9b74267956a4 completed April 3, 2026, 11:56 a.m.
Created at: March 30, 2026, 5:20 p.m.