Triple

T12816983
Position Surface form Disambiguated ID Type / Status
Subject Tübingen E306426 entity
Predicate hasLandmark P105 FINISHED
Object Neckarfront E611654 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: Neckarfront | Statement: [Tübingen, hasLandmark, Neckarfront]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neckarfront
Context triple: [Tübingen, hasLandmark, Neckarfront]
  • A. Neckarfront chosen
    The Neckarfront is a picturesque row of historic houses lining the Neckar River in Tübingen, Germany, and is one of the city's most iconic views.
  • B. Seelitz
    Seelitz is a municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the Mittelsachsen region.
  • C. Erasbach
    Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
  • D. Langfuhr
    Langfuhr is a Canadian-bred Thoroughbred racehorse and successful sire known for his multiple Grade I sprint victories in the United States.
  • E. Helmbrechts
    Helmbrechts is a small town in northern Bavaria, Germany, known for its textile industry and location in the Franconian Forest 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e9d00088190ac0f5d60e1de7a7c completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ecee33c8190a6bf045731bb9326 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:31 p.m.