Triple

T11909534
Position Surface form Disambiguated ID Type / Status
Subject Monotype E283356 entity
Predicate publishes P80 FINISHED
Object Arial
Arial is a widely used sans-serif typeface known for its clean, modern appearance and extensive use in digital and print media.
 E954365 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: Arial | Statement: [Monotype, publishes, Arial]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Arial
Context triple: [Monotype, publishes, Arial]
  • A. 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.
  • 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. Lato
    Lato is a Polish surname most famously borne by Grzegorz Lato, a legendary Polish footballer and World Cup Golden Boot winner.
  • E. Frutiger
    Frutiger is a widely used humanist sans-serif typeface designed by Adrian Frutiger, known for its clarity and legibility in signage and print.
  • 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: Arial
Triple: [Monotype, publishes, Arial]
Generated description
Arial is a widely used sans-serif typeface known for its clean, modern appearance and extensive use in digital and print media.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Arial
Target entity description: Arial is a widely used sans-serif typeface known for its clean, modern appearance and extensive use in digital and print media.
  • A. 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.
  • 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. Lato
    Lato is a Polish surname most famously borne by Grzegorz Lato, a legendary Polish footballer and World Cup Golden Boot winner.
  • E. Frutiger
    Frutiger is a widely used humanist sans-serif typeface designed by Adrian Frutiger, known for its clarity and legibility in signage and print.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e5278eb081909a7ecfe38beeeda9 completed April 10, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69f44004b454819091b41bac99895106 completed May 1, 2026, 5:54 a.m.
NEDg Description generation batch_69f448fa8eec81909fe6ac0902f46998 completed May 1, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69f44aef15148190ba8090681b921ffa completed May 1, 2026, 6:40 a.m.
Created at: April 8, 2026, 9:44 p.m.