Triple

T3884633
Position Surface form Disambiguated ID Type / Status
Subject Hugo Steinhaus E92909 entity
Predicate givenName P17 FINISHED
Object Hugo E37442 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: Hugo | Statement: [Hugo Steinhaus, givenName, Hugo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hugo
Context triple: [Hugo Steinhaus, givenName, Hugo]
  • A. Hugo chosen
    Hugo is a masculine given name of Germanic origin, commonly used in various European and Spanish-speaking countries.
  • B. Hugo
    Hugo is a 2011 fantasy adventure film directed by Martin Scorsese, acclaimed for its innovative use of 3D and its homage to early cinema and filmmaker Georges Méliès.
  • C. The Wonder
    The Wonder is a psychological period drama film in which Florence Pugh plays an English nurse sent to investigate a young Irish girl who appears to survive without eating.
  • D. The Light
    The Light is a notable work by the rapper Common, showcasing his introspective lyricism and soulful, jazz-influenced hip-hop style.
  • E. The Light
    The Light is a work by author W. Jeffrey, likely a novel or story centered on themes of illumination, revelation, or spiritual insight.
  • 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeec92cc548190b88b899299e5ccdc completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5125bee048190ba7553797e9fd254 completed March 14, 2026, 7:46 a.m.
Created at: March 9, 2026, 3:20 p.m.