Triple

T1769281
Position Surface form Disambiguated ID Type / Status
Subject Chula Vista E38835 entity
Predicate abbreviation P43 FINISHED
Object CV
CV is a common abbreviation for Chula Vista, a coastal city in Southern California located just south of San Diego.
 E200124 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: CV | Statement: [Chula Vista, abbreviation, CV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CV
Context triple: [Chula Vista, abbreviation, CV]
  • A. C.V.
    C.V. is the autobiographical section of Stephen King’s book "On Writing," in which he recounts key experiences from his life that shaped him as a writer.
  • B. CAREER
    CAREER is a prestigious National Science Foundation program that supports early-career faculty in building a foundation for a lifetime of leadership in research and education.
  • C. Portfolio
    Portfolio is a business-focused imprint of Penguin Random House known for publishing books on leadership, entrepreneurship, and innovation.
  • D. CVG
    CVG is the IATA airport code for Cincinnati/Northern Kentucky International Airport, a major air transport hub serving the Greater Cincinnati metropolitan area.
  • E. LinkedIn
    LinkedIn is a professional networking platform and social media service focused on careers, business connections, and job opportunities.
  • 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: CV
Triple: [Chula Vista, abbreviation, CV]
Generated description
CV is a common abbreviation for Chula Vista, a coastal city in Southern California located just south of San Diego.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CV
Target entity description: CV is a common abbreviation for Chula Vista, a coastal city in Southern California located just south of San Diego.
  • A. C.V.
    C.V. is the autobiographical section of Stephen King’s book "On Writing," in which he recounts key experiences from his life that shaped him as a writer.
  • B. CAREER
    CAREER is a prestigious National Science Foundation program that supports early-career faculty in building a foundation for a lifetime of leadership in research and education.
  • C. Portfolio
    Portfolio is a business-focused imprint of Penguin Random House known for publishing books on leadership, entrepreneurship, and innovation.
  • D. CVG
    CVG is the IATA airport code for Cincinnati/Northern Kentucky International Airport, a major air transport hub serving the Greater Cincinnati metropolitan area.
  • E. LinkedIn
    LinkedIn is a professional networking platform and social media service focused on careers, business connections, and job opportunities.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa648d9f2c8190aca4884648a69eb0 completed March 6, 2026, 5:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada991564c81909ae00fdcb47f52af completed March 8, 2026, 4:53 p.m.
NEDg Description generation batch_69adab0295b8819092cb51082337b97b completed March 8, 2026, 4:59 p.m.
NED2 Entity disambiguation (via description) batch_69adaea83bfc8190a526d5f2bd460e4c completed March 8, 2026, 5:15 p.m.
Created at: March 4, 2026, 7:31 p.m.