Triple

T853353
Position Surface form Disambiguated ID Type / Status
Subject Ralph Merkle E18435 entity
Predicate employer P7 FINISHED
Object Zyvex
Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
 E99145 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: Zyvex | Statement: [Ralph Merkle, employer, Zyvex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zyvex
Context triple: [Ralph Merkle, employer, Zyvex]
  • A. Onex
    Onex is a suburban municipality in western Switzerland located just outside the city of Geneva.
  • B. Ornex
    Ornex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • C. Astralwerks
    Astralwerks is an American record label known for releasing influential electronic and dance music from prominent artists and producers.
  • D. Litovel
    Litovel is a historic town in the Olomouc Region of the Czech Republic, known for its traditional architecture and local brewery.
  • E. Obvious Corporation
    Obvious Corporation was the early holding company and development vehicle created by Twitter’s founders that incubated and spun out Twitter as an independent company.
  • 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: Zyvex
Triple: [Ralph Merkle, employer, Zyvex]
Generated description
Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zyvex
Target entity description: Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
  • A. Onex
    Onex is a suburban municipality in western Switzerland located just outside the city of Geneva.
  • B. Ornex
    Ornex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • C. Astralwerks
    Astralwerks is an American record label known for releasing influential electronic and dance music from prominent artists and producers.
  • D. Litovel
    Litovel is a historic town in the Olomouc Region of the Czech Republic, known for its traditional architecture and local brewery.
  • E. Obvious Corporation
    Obvious Corporation was the early holding company and development vehicle created by Twitter’s founders that incubated and spun out Twitter as an independent company.
  • 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_69a4938bdd3c8190a954a3c11844d9cf completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac389a44819093396a58d2afa700 completed March 1, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a792a29f448190b96d934656e5399e completed March 4, 2026, 2:02 a.m.
NEDg Description generation batch_69a79335d99c819098c72e7a86ad1130 completed March 4, 2026, 2:04 a.m.
NED2 Entity disambiguation (via description) batch_69a793c612d88190bce254142bd75f67 completed March 4, 2026, 2:07 a.m.
Created at: March 1, 2026, 7:39 p.m.