Triple

T9487153
Position Surface form Disambiguated ID Type / Status
Subject Mostviertel E228789 entity
Predicate majorTown P316 FINISHED
Object Amstetten E248695 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: Amstetten | Statement: [Mostviertel, majorTown, Amstetten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amstetten
Context triple: [Mostviertel, majorTown, Amstetten]
  • A. Amstetten chosen
    Amstetten is a town in northeastern Austria that serves as an important regional transport and commercial hub between Linz and Vienna.
  • B. 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.
  • C. Gmunden
    Gmunden is a picturesque town in Upper Austria known for its lakeside setting on the Traunsee and its historic ceramics industry.
  • D. Wiener Neustadt
    Wiener Neustadt is a historic city in Lower Austria known as a former imperial residence and military stronghold south of Vienna.
  • E. Vöcklabruck
    Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
  • 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_69ca847424f081908180305555139f7a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd8051303881909566126a2688e41c completed April 1, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d178e38d488190a4bc594b12a44baf completed April 4, 2026, 8:47 p.m.
Created at: March 30, 2026, 7:55 p.m.