Triple

T16471338
Position Surface form Disambiguated ID Type / Status
Subject Enzkreis E400067 entity
Predicate hasRiver P165 FINISHED
Object Nagold E95811 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: Nagold | Statement: [Enzkreis, hasRiver, Nagold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagold
Context triple: [Enzkreis, hasRiver, Nagold]
  • A. Nagold chosen
    Nagold is a river in southwestern Germany that flows through the Black Forest region before joining the Enz River.
  • B. Könnern
    Könnern is a small town in the German state of Saxony-Anhalt, known for its rural character and location near the Saale River.
  • C. Winnental
    Winnental is a historical town that served as the capital of the former German territory of Württemberg-Winnental.
  • D. Reichenau
    Reichenau is a German municipality best known for its UNESCO-listed monastic island on Lake Constance, renowned for its medieval abbey and cultural heritage.
  • E. Reichenau
    Reichenau is a locality in the Swiss canton of Graubünden known as the meeting point of the Vorderrhein and Hinterrhein rivers, which together form the Rhine.
  • 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_6a00581c24508190b4888357828fed80 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:11 a.m.