Triple

T11231706
Position Surface form Disambiguated ID Type / Status
Subject Grzegorz Lato E265836 entity
Predicate familyName P18 FINISHED
Object Lato E265836 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: Lato | Statement: [Grzegorz Lato, familyName, Lato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lato
Context triple: [Grzegorz Lato, familyName, Lato]
  • A. Lato chosen
    Lato is a Polish surname most famously borne by Grzegorz Lato, a legendary Polish footballer and World Cup Golden Boot winner.
  • B. Avenir
    Avenir is Buick’s top-tier luxury sub-brand and trim line, offering more premium materials, advanced features, and upscale styling than the brand’s standard models.
  • C. Gill Sans
    Gill Sans is a widely used British humanist sans-serif typeface designed by Eric Gill, known for its clean, modern look and extensive use in signage and branding.
  • D. Libre Baskerville
    Libre Baskerville is an open-source, web-optimized serif typeface that adapts the classic Baskerville design for modern digital use.
  • E. Helvetica
    Helvetica is a widely used sans-serif typeface known for its clean, modern, and highly legible design, commonly seen in corporate branding and public signage worldwide.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9026e1c81909456ac946bbba972 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad49b5cc8190b99cb2cd8de72109 completed April 19, 2026, 10:24 a.m.
Created at: April 8, 2026, 9:30 p.m.