Triple

T8735307
Position Surface form Disambiguated ID Type / Status
Subject Essling E207367 entity
Predicate partOf P40 FINISHED
Object Donaustadt E386464 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: Donaustadt | Statement: [Essling, partOf, Donaustadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donaustadt
Context triple: [Essling, partOf, Donaustadt]
  • A. Donaustadt chosen
    Donaustadt is the 22nd district of Vienna, Austria, known for its extensive residential areas, modern developments, and the location of the Vienna International Centre.
  • B. Döbling
    Döbling is a residential district in the northwest of Vienna, Austria, known for its vineyards, green hills, and affluent neighborhoods.
  • C. Schwechat
    Schwechat is an Austrian town just southeast of Vienna, best known as the site of Vienna International Airport and a major hub for industry and transport.
  • D. 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.
  • E. Seibersdorf
    Seibersdorf is an Austrian town known for hosting major research and testing laboratories of the International Atomic Energy Agency.
  • 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_69ca8358e4008190898471a59b96c301 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d2b89988190bb7671e273026046 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf88dc7ba88190865957c8d344fa00 completed April 3, 2026, 9:31 a.m.
Created at: March 30, 2026, 6:37 p.m.