Triple

T14210332
Position Surface form Disambiguated ID Type / Status
Subject István Széchenyi E352210 entity
Predicate placeOfDeath P21 FINISHED
Object Döbling E519311 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: Döbling | Statement: [István Széchenyi, placeOfDeath, Döbling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Döbling
Context triple: [István Széchenyi, placeOfDeath, Döbling]
  • A. Döbling chosen
    Döbling is a residential district in the northwest of Vienna, Austria, known for its vineyards, green hills, and affluent neighborhoods.
  • B. Meidling
    Meidling is a residential and historically working-class district in the southwest of Vienna, Austria, known for its dense urban fabric and good public transport connections.
  • C. Ottakring
    Ottakring is a diverse, traditionally working-class district in western Vienna known for its multicultural atmosphere, historic brewery, and vibrant urban life.
  • D. Donaustadt
    Donaustadt is the 22nd district of Vienna, Austria, known for its extensive residential areas, modern developments, and the location of the Vienna International Centre.
  • E. 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.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61fa8d24819092a8ec5d34c1c799 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd19557f908190abb3dc116676f215 completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:05 a.m.