Triple

T4021780
Position Surface form Disambiguated ID Type / Status
Subject Theresian Military Academy E91294 entity
Predicate locatedIn P40 FINISHED
Object Wiener Neustadt E175023 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: Wiener Neustadt | Statement: [Theresian Military Academy, locatedIn, Wiener Neustadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wiener Neustadt
Context triple: [Theresian Military Academy, locatedIn, Wiener Neustadt]
  • A. Wiener Neustadt chosen
    Wiener Neustadt is a historic city in Lower Austria known as a former imperial residence and military stronghold south of Vienna.
  • B. Mödling
    Mödling is a historic town in Lower Austria, near Vienna, known for its picturesque old town, wine culture, and proximity to the Vienna Woods.
  • C. Seibersdorf
    Seibersdorf is an Austrian town known for hosting major research and testing laboratories of the International Atomic Energy Agency.
  • D. Tulln an der Donau
    Tulln an der Donau is an Austrian town on the Danube River, known for its rich history and as the birthplace of painter Egon Schiele.
  • E. 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.
  • 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_69aed9618b04819081750d979d2af098 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefacb4c208190b8dd595a534850b2 completed March 9, 2026, 4:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5768fae4881908c9dea4e39e3788c completed March 14, 2026, 2:54 p.m.
Created at: March 9, 2026, 3:35 p.m.