Triple

T5948765
Position Surface form Disambiguated ID Type / Status
Subject Newcastle-under-Lyme E132343 entity
Predicate hasTwinTown P919 FINISHED
Object Schwerte E496588 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: Schwerte | Statement: [Newcastle-under-Lyme, hasTwinTown, Schwerte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwerte
Context triple: [Newcastle-under-Lyme, hasTwinTown, Schwerte]
  • A. Schwerte chosen
    Schwerte is a town in North Rhine-Westphalia, Germany, known as a small industrial and commuter community near Dortmund.
  • B. Siegburg
    Siegburg is a historic town in North Rhine-Westphalia, Germany, known for its medieval abbey and location near Bonn and Cologne.
  • C. Solingen
    Solingen is a city in western Germany renowned for its centuries-old blade-making tradition and production of high-quality knives and swords.
  • D. Siegen
    Siegen is a city in western Germany known as the birthplace of the Baroque painter Peter Paul Rubens and for its historic mining and university traditions.
  • E. Kleve
    Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
  • 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0397deea08190b9397d0413740300 completed March 22, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c08d4f0481908547609bc2736380 completed March 23, 2026, 4:24 a.m.
Created at: March 22, 2026, 4:01 p.m.