Triple

T12641496
Position Surface form Disambiguated ID Type / Status
Subject Viktor Kaplan E301907 entity
Predicate placeOfBirth P1 FINISHED
Object Mürzzuschlag E474492 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: Mürzzuschlag | Statement: [Viktor Kaplan, placeOfBirth, Mürzzuschlag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mürzzuschlag
Context triple: [Viktor Kaplan, placeOfBirth, Mürzzuschlag]
  • A. Mürzzuschlag chosen
    Mürzzuschlag is a small Austrian town in the state of Styria, known historically for its iron industry and as a winter sports and railway hub in the Eastern Alps.
  • B. Mürz
    Mürz is a river in southeastern Austria that flows through the state of Styria and is an important tributary of the Mur River.
  • C. Schönbichl
    Schönbichl is a small island located in the Eibsee, a picturesque alpine lake at the foot of Germany’s Zugspitze mountain.
  • D. Bad Salzungen
    Bad Salzungen is a spa town in Thuringia, Germany, known for its saline springs and therapeutic health resorts.
  • E. Leißling
    Leißling is a small municipality in the Weißenfels area of Saxony-Anhalt, Germany, known for its local industry and residential character.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9614ae6ac8190b42acbf2b0331fda completed April 10, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6687770388190b4777885dae8a38f completed May 2, 2026, 9:11 p.m.
Created at: April 9, 2026, 5:17 p.m.