Triple

T2556806
Position Surface form Disambiguated ID Type / Status
Subject Symbian E56746 entity
Predicate usedByManufacturer P5104 FINISHED
Object Sharp
Sharp is a Japanese electronics manufacturer best known for producing consumer devices such as mobile phones, televisions, and display technologies.
 E277046 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: Sharp | Statement: [Symbian, usedByManufacturer, Sharp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sharp
Context triple: [Symbian, usedByManufacturer, Sharp]
  • A. Sharp
    Sharp is a common English surname borne by numerous notable individuals across politics, sports, academia, and the arts.
  • B. Sharpness
    Sharpness is a small port village in Gloucestershire, England, situated on the River Severn and known historically as a key inland dock and terminus for canal traffic.
  • C. Blunt
    Blunt is an English surname borne by various notable figures in the arts, politics, and public life.
  • D. Quick
    Quick is the fast-talking, street-smart protagonist played by Eddie Murphy in the 1989 crime-comedy film "Harlem Nights."
  • E. Slash
    Slash is a renowned rock guitarist best known as the lead guitarist of Guns N' Roses, celebrated for his iconic riffs and top-hatted stage persona.
  • 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: Sharp
Triple: [Symbian, usedByManufacturer, Sharp]
Generated description
Sharp is a Japanese electronics manufacturer best known for producing consumer devices such as mobile phones, televisions, and display technologies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sharp
Target entity description: Sharp is a Japanese electronics manufacturer best known for producing consumer devices such as mobile phones, televisions, and display technologies.
  • A. Sharp
    Sharp is a common English surname borne by numerous notable individuals across politics, sports, academia, and the arts.
  • B. Sharpness
    Sharpness is a small port village in Gloucestershire, England, situated on the River Severn and known historically as a key inland dock and terminus for canal traffic.
  • C. Blunt
    Blunt is an English surname borne by various notable figures in the arts, politics, and public life.
  • D. Quick
    Quick is the fast-talking, street-smart protagonist played by Eddie Murphy in the 1989 crime-comedy film "Harlem Nights."
  • E. Slash
    Slash is a renowned rock guitarist best known as the lead guitarist of Guns N' Roses, celebrated for his iconic riffs and top-hatted stage persona.
  • 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_69ab4a4bfec081908039988ec4c86e28 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd310b3a48190b275be13eb050e57 completed March 7, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5d1d937c8190ac6b7bb405a49c3c completed March 9, 2026, 11:51 p.m.
NEDg Description generation batch_69af5dc7ef4c81908581716c07dcae47 completed March 9, 2026, 11:54 p.m.
NED2 Entity disambiguation (via description) batch_69af5e66a39c81909a49c272cd595c84 completed March 9, 2026, 11:57 p.m.
Created at: March 6, 2026, 9:48 p.m.