Triple

T8455660
Position Surface form Disambiguated ID Type / Status
Subject Emilie Benes Brzezinski E199912 entity
Predicate placeOfBirth P1 FINISHED
Object Geneva E414 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: Geneva | Statement: [Emilie Benes Brzezinski, placeOfBirth, Geneva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geneva
Context triple: [Emilie Benes Brzezinski, placeOfBirth, Geneva]
  • A. Geneva chosen
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • B. Geneva
    Geneva is a small city in northeastern Ohio situated along Lake Erie, known for its wineries, tourism, and location within the Rust Belt region.
  • C. Geneva
    Geneva is a small city in New York's Finger Lakes region, known for its lakeside setting on Seneca Lake and its historic colleges and wineries.
  • D. Berne
    Berne is the de facto capital city of Switzerland and the seat of its federal government institutions.
  • E. Lausanne
    Lausanne is a major Swiss city on the shores of Lake Geneva, known for hosting the International Olympic Committee and its vibrant cultural and academic institutions.
  • 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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe48e0ae481908b40f7f124b0551e completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecc1842608190bc0fd78e28aa324d completed April 2, 2026, 8:05 p.m.
Created at: March 30, 2026, 6:10 p.m.