Triple

T5874923
Position Surface form Disambiguated ID Type / Status
Subject Ernő Goldfinger E130602 entity
Predicate givenName P17 FINISHED
Object Ernő
Ernő is a Hungarian-born British modernist architect best known for his influential and often controversial Brutalist buildings in London.
 E563355 NE FINISHED

How this triple was built (4 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: Ernő | Statement: [Ernő Goldfinger, givenName, Ernő]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ernő
Context triple: [Ernő Goldfinger, givenName, Ernő]
  • A. László
    László is a Hungarian given name most famously borne by the avant-garde artist and Bauhaus teacher László Moholy-Nagy.
  • B. György
    György is a Hungarian given name commonly used for men, equivalent to the English name George.
  • C. István
    István is the Hungarian given name of Stephen I of Hungary, the first Christian king and founder of the medieval Hungarian state.
  • D. Kálmán
    Kálmán is a Hungarian surname most notably associated with Rudolf E. Kálmán, the pioneering engineer and mathematician behind the Kalman filter.
  • E. Jenő
    Jenő is the Hungarian given name of the renowned theoretical physicist and mathematician Wigner Jenő Pál, known in English as Eugene Wigner.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ernő
Triple: [Ernő Goldfinger, givenName, Ernő]
Generated description
Ernő is a Hungarian-born British modernist architect best known for his influential and often controversial Brutalist buildings in London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ernő
Target entity description: Ernő is a Hungarian-born British modernist architect best known for his influential and often controversial Brutalist buildings in London.
  • A. László
    László is a Hungarian given name most famously borne by the avant-garde artist and Bauhaus teacher László Moholy-Nagy.
  • B. György
    György is a Hungarian given name commonly used for men, equivalent to the English name George.
  • C. István
    István is the Hungarian given name of Stephen I of Hungary, the first Christian king and founder of the medieval Hungarian state.
  • D. Kálmán
    Kálmán is a Hungarian surname most notably associated with Rudolf E. Kálmán, the pioneering engineer and mathematician behind the Kalman filter.
  • E. Jenő
    Jenő is the Hungarian given name of the renowned theoretical physicist and mathematician Wigner Jenő Pál, known in English as Eugene Wigner.
  • F. None of above. chosen

Provenance (5 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_69c0085523688190bfd487479ce819e6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c035fc86308190851b282456bcd715 completed March 22, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1134bb82881908b912f96a3b6f0f1 completed March 23, 2026, 10:17 a.m.
NEDg Description generation batch_69c113c9bc048190ab517300d56dd8e0 completed March 23, 2026, 10:19 a.m.
NED2 Entity disambiguation (via description) batch_69c1144e77f881908ab59a67160c1630 completed March 23, 2026, 10:22 a.m.
Created at: March 22, 2026, 3:57 p.m.