Triple

T9487294
Position Surface form Disambiguated ID Type / Status
Subject Vienna Woods E228792 entity
Predicate partlyLocatedIn P40 FINISHED
Object Vienna (federal state) E279838 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: Vienna (federal state) | Statement: [Vienna Woods, partlyLocatedIn, Vienna (federal state)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vienna (federal state)
Context triple: [Vienna Woods, partlyLocatedIn, Vienna (federal state)]
  • A. Vienna (state) chosen
    Vienna (state) is Austria’s smallest federal state and its capital city, serving as the country’s political, cultural, and economic center.
  • B. Austria Wien
    Austria Wien is a major Viennese football club and one of Austria’s most successful and historic teams.
  • C. Wiener Neustadt
    Wiener Neustadt is a historic city in Lower Austria known as a former imperial residence and military stronghold south of Vienna.
  • D. Vienna
    Vienna is a small town in Dane County, Wisconsin, known for its rural character and proximity to the Madison metropolitan area.
  • E. Vienna
    Vienna is the capital city of Austria, renowned for its rich imperial history, classical music heritage, and vibrant cultural and intellectual life.
  • 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_69d12d18fd908190b562fa0a8dad7c63 completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:55 p.m.