Triple

T13229208
Position Surface form Disambiguated ID Type / Status
Subject Emmy Hennings E314963 entity
Predicate wasActiveIn P7685 FINISHED
Object Zürich E13407 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: Zürich | Statement: [Emmy Hennings, wasActiveIn, Zürich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zürich
Context triple: [Emmy Hennings, wasActiveIn, Zürich]
  • A. Zurich chosen
    Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
  • B. Stettlen
    Stettlen is a municipality in the canton of Bern in Switzerland, situated just east of the city of Bern and functioning largely as a residential and commuter community.
  • C. Berne
    Berne is the de facto capital city of Switzerland and the seat of its federal government institutions.
  • D. Basel-Stadt
    Basel-Stadt is a small, urban Swiss canton centered on the city of Basel, a major cultural and economic hub in northwestern Switzerland.
  • E. Schaffhausen
    Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d336ae08190bfc118cfbefddf84 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8c0b24c819082d0ec947b7d99ea completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 9:21 p.m.