Triple

T15634650
Position Surface form Disambiguated ID Type / Status
Subject Nister E375907 entity
Predicate flowsNear P350 FINISHED
Object Hachenburg E1039722 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: Hachenburg | Statement: [Nister, flowsNear, Hachenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hachenburg
Context triple: [Nister, flowsNear, Hachenburg]
  • A. Hachenburg chosen
    Hachenburg is a historic small town in the Westerwald region of Rhineland-Palatinate, Germany, known for its medieval town center and hilltop castle.
  • B. Langenhain
    Langenhain is a district of the town Hofheim am Taunus in the German state of Hesse, known for its residential character and proximity to the Taunus hills.
  • C. Hornsberg
    Hornsberg is a waterfront residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • D. Hagsdorf
    Hagsdorf is a small locality that forms part of the municipality of Persenbeug-Gottsdorf in Lower Austria.
  • E. Kottenheim
    Kottenheim is a small municipality in western Germany’s Rhineland-Palatinate region, known for its volcanic landscape and traditional stone quarrying.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04eb8b4c48190b80fea6877483089 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c4303888190a93830ef534715ae completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 4:14 a.m.