Triple

T16471339
Position Surface form Disambiguated ID Type / Status
Subject Enzkreis E400067 entity
Predicate hasRiver P165 FINISHED
Object Pfinz E403155 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: Pfinz | Statement: [Enzkreis, hasRiver, Pfinz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pfinz
Context triple: [Enzkreis, hasRiver, Pfinz]
  • A. Pfinz chosen
    Pfinz is a river in Baden-Württemberg, Germany, that flows through the northern Black Forest region and the Karlsruhe area before joining the Enz.
  • B. Eschwege
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • C. Appenweier
    Appenweier is a municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenau district near the Rhine and the French border.
  • D. Weidach
    Weidach is a locality or district that forms part of the municipality of Blaustein in the state of Baden-Württemberg, Germany.
  • E. Schönbuch
    Schönbuch is a large forest and nature reserve in the German state of Baden-Württemberg, known for its extensive woodlands, wildlife, and recreational hiking areas.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32dd0d2fc81909b68b5afb00f192f completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00679ecf4c819096e7f698b81fe25a completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:11 a.m.