Triple

T23008868
Position Surface form Disambiguated ID Type / Status
Subject Charles Simonyi E572851 entity
Predicate hasSurname P18 FINISHED
Object Simonyi NE NERFINISHED

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: Simonyi | Statement: [Charles Simonyi, hasSurname, Simonyi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simonyi
Context triple: [Charles Simonyi, hasSurname, Simonyi]
  • A. Simonyi chosen
    Simonyi is a Hungarian surname most prominently associated with Charles Simonyi, a software architect and early Microsoft pioneer known for his work on Microsoft Office and for being a space tourist.
  • B. Sarközy de Nagy-Bocsa
    Sarközy de Nagy-Bocsa is the Hungarian-origin aristocratic family name of former French president Nicolas Sarkozy.
  • C. Várkonyi
    Várkonyi is a Hungarian surname most notably borne by the early 20th-century film and stage actor Victor Varconi.
  • D. Bulcsú
    Bulcsú was a prominent 10th-century Hungarian chieftain and military leader known for his role in the Magyar raids into Western Europe.
  • E. Alvinczi
    Alvinczi is the surname of Josef Alvinczi, an 18th-century Austrian field marshal of Hungarian origin who served in the Habsburg military during the French Revolutionary Wars.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b764cc8190a51be76f1d9611e1 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1835919b08190ba78e182b87358d4 completed April 29, 2026, 4:04 a.m.
Created at: April 17, 2026, 3:51 p.m.