Triple

T11133305
Position Surface form Disambiguated ID Type / Status
Subject Unstrut E263342 entity
Predicate flowsThrough P225 FINISHED
Object Laucha an der Unstrut E709158 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: Laucha an der Unstrut | Statement: [Unstrut, flowsThrough, Laucha an der Unstrut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laucha an der Unstrut
Context triple: [Unstrut, flowsThrough, Laucha an der Unstrut]
  • A. Laucha an der Unstrut chosen
    Laucha an der Unstrut is a small town in Saxony-Anhalt, Germany, known for its location along the Unstrut River in a historic wine-growing and cultural landscape.
  • B. Lauingen
    Lauingen is a historic Bavarian town in southern Germany, best known as the birthplace of the medieval scholar and philosopher Albert the Great.
  • C. Wittenau
    Wittenau is a locality in the Reinickendorf borough of Berlin, Germany, known primarily as a residential area with good transport connections.
  • D. Lichtenfels
    Lichtenfels is a town in the Upper Franconia region of Bavaria, Germany, known for its basket-making tradition and historic architecture.
  • E. Trakehnen
    Trakehnen was a renowned East Prussian stud farm and village, historically famous as the cradle of the Trakehner horse breed.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8347a248190837e8c26f25f553a completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e46308d2f481908827d0d569802f89 completed April 19, 2026, 5:07 a.m.
Created at: April 8, 2026, 9:28 p.m.