Triple

T14755212
Position Surface form Disambiguated ID Type / Status
Subject Margareten E346712 entity
Predicate nativeName P15 FINISHED
Object Margareten E346712 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: Margareten | Statement: [Margareten, nativeName, Margareten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margareten
Context triple: [Margareten, nativeName, Margareten]
  • A. Margareten chosen
    Margareten is the 5th district of Vienna, Austria, known as a densely populated, traditionally working-class area that has undergone significant urban renewal and gentrification.
  • B. St. Margrethen
    St. Margrethen is a municipality in the canton of St. Gallen in northeastern Switzerland, located near the Austrian border along the Rhine River.
  • C. Magdelon
    Magdelon is one of the two naive, pretentious young women satirized for their affected manners and romantic fantasies in Molière’s comedy *Les Précieuses ridicules*.
  • D. Leitha
    Leitha is a river in Central Europe that flows through Austria and Hungary and serves as part of the historical border between the two countries.
  • E. Veleslavín
    Veleslavín is a residential district in the northwestern part of Prague known for its transport connections and proximity to green areas.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7d59df08190a86da5048358bd6e completed April 14, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb9e1b8481909abea3daabe91302 completed May 8, 2026, 3:05 p.m.
Created at: April 10, 2026, 1:30 a.m.