Triple

T18481456
Position Surface form Disambiguated ID Type / Status
Subject Austrian Autobahn network E451568 entity
Predicate servesCity P82 FINISHED
Object Linz NE NERFINISHED

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: Linz | Statement: [Austrian Autobahn network, servesCity, Linz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linz
Context triple: [Austrian Autobahn network, servesCity, Linz]
  • A. Linz chosen
    Linz is a major Austrian city known for its industrial heritage, vibrant cultural scene, and location along the Danube River.
  • B. Donaustauf
    Donaustauf is a market town in Bavaria, Germany, situated on the Danube River just east of the city of Regensburg and known for the nearby Walhalla memorial.
  • C. Klagenfurt
    Klagenfurt is the capital city of the Austrian state of Carinthia, known for its historic old town and proximity to Lake Wörthersee.
  • D. St. Pölten
    St. Pölten is the capital city of the Austrian state of Lower Austria, known for its baroque architecture and role as a regional administrative and cultural center.
  • E. Lenzburg
    Lenzburg is a historic Swiss town in the canton of Aargau, known for its medieval hilltop castle and well-preserved old town.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38465a0819099b9b42d2a662ac1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e531d3d13c81909c52d797360b840a completed April 19, 2026, 7:49 p.m.
Created at: April 10, 2026, 11:35 a.m.