Triple

T14199197
Position Surface form Disambiguated ID Type / Status
Subject Bundesstraße 9 E351918 entity
Predicate connects P390 FINISHED
Object Kleve E233215 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: Kleve | Statement: [Bundesstraße 9, connects, Kleve]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kleve
Context triple: [Bundesstraße 9, connects, Kleve]
  • A. Kleve chosen
    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.
  • B. Gescher
    Gescher is a small town in western Germany’s Münsterland region, noted for its traditional bell foundries and rural character.
  • C. Gevelsberg
    Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
  • D. Schlettstadt
    Schlettstadt, now known as Sélestat, is a historic town in the Alsace region of northeastern France noted for its medieval architecture and humanist heritage.
  • E. Jülich
    Jülich is a historic town in western Germany, known for its former status as a ducal residence and its significant Renaissance-era fortifications.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61f472548190a1a7edc40526eac3 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbb445a48190ba3dafb1f076ac83 completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 1:04 a.m.