Triple

T12406340
Position Surface form Disambiguated ID Type / Status
Subject Werra-Meißner-Kreis E296396 entity
Predicate containsRiver P165 FINISHED
Object Werra E112665 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: Werra | Statement: [Werra-Meißner-Kreis, containsRiver, Werra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Werra
Context triple: [Werra-Meißner-Kreis, containsRiver, Werra]
  • A. Werra chosen
    The Werra is a major river in central Germany that forms one of the two headstreams of the Weser.
  • B. Jagst
    The Jagst is a river in Baden-Württemberg, Germany, known as one of the major right-bank tributaries of the Neckar and flowing through a largely rural, scenic landscape.
  • C. Regnitz
    The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
  • D. Neckar
    The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
  • E. Wupper
    The Wupper is a river in North Rhine-Westphalia, Germany, known for flowing through the industrial city of Wuppertal and its surrounding region.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d48f1908190918551c794f98fe3 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78ac6efe88190b48d2868443ed412 completed May 3, 2026, 5:49 p.m.
Created at: April 8, 2026, 9:55 p.m.