Triple

T14978019
Position Surface form Disambiguated ID Type / Status
Subject Salzkammergut railway E373502 entity
Predicate passesThrough P225 FINISHED
Object Ebensee E964827 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: Ebensee | Statement: [Salzkammergut railway, passesThrough, Ebensee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ebensee
Context triple: [Salzkammergut railway, passesThrough, Ebensee]
  • A. Ebensee chosen
    Ebensee is an Austrian town in the Salzkammergut region, known for its lakeside setting amid the Alps and its historical significance including a former World War II concentration camp site.
  • B. Eibsee
    Eibsee is a picturesque alpine lake in Bavaria, Germany, renowned for its clear turquoise waters and dramatic setting at the foot of the Zugspitze.
  • C. Geiseltalsee
    Geiseltalsee is a large artificial lake in Saxony-Anhalt, Germany, created by flooding a former lignite mining area and now used for recreation and nature conservation.
  • D. Scharmützelsee
    Scharmützelsee is a popular lake in eastern Germany known for its scenic surroundings, recreational activities, and spa resorts.
  • E. Riegsee
    Riegsee is a picturesque lake in Bavaria, Germany, known for its clear waters and scenic Alpine surroundings.
  • 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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6fbd138819092254ea37388026c completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69febfd3ebd08190a2b7c70c2ba6deb3 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 2:51 a.m.