Triple

T11979567
Position Surface form Disambiguated ID Type / Status
Subject Bolivian Primera División E285121 entity
Predicate hasMemberClub P28388 FINISHED
Object Aurora
Aurora is a Bolivian professional football club that competes in the country's top-tier league.
E831035 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: Aurora | Statement: [Bolivian Primera División, hasMemberClub, Aurora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aurora
Context triple: [Bolivian Primera División, hasMemberClub, Aurora]
  • A. Aurora
    Aurora is a major suburban city in the Denver metropolitan area of Colorado, known for its diverse population, extensive parks and open spaces, and role as a key economic and residential hub on the eastern side of the metro region.
  • B. Aurora
    Aurora is a coastal province in the Philippines known for its Pacific shoreline, surfing spots like Baler, and lush mountainous landscapes.
  • C. Aurora
    Aurora is a mystical and theosophical treatise by Jakob Böhme that explores the nature of God, creation, and spiritual rebirth through symbolic and visionary theology.
  • D. Aurora
    Aurora is the Roman goddess of the dawn, who renews herself each morning and announces the arrival of the sun.
  • E. Aurora
    Aurora is one of the official mascots of the Salt Lake City 2002 Winter Olympics, represented as an animal character symbolizing the spirit and culture of the Games.
  • 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: Aurora
Triple: [Bolivian Primera División, hasMemberClub, Aurora]
Generated description
Aurora is a Bolivian professional football club that competes in the country's top-tier league.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Aurora
Target entity description: Aurora is a Bolivian professional football club that competes in the country's top-tier league.
  • A. Aurora chosen
    Aurora is a Bolivian football club commonly known by its short name, Aurora.
  • B. Aurora
    Aurora is a major suburban city in the Denver metropolitan area of Colorado, known for its diverse population, extensive parks and open spaces, and role as a key economic and residential hub on the eastern side of the metro region.
  • C. Aurora
    Aurora is a suburban town in central York Region, Ontario, known as an affluent residential community within the Greater Toronto Area.
  • D. Aurora
    Aurora is a coastal province in the Philippines known for its Pacific shoreline, surfing spots like Baler, and lush mountainous landscapes.
  • E. Aurora
    Aurora is a major city in northeastern Illinois, known as a key suburb of Chicago and a regional center for industry, transportation, and technology.
  • F. None of above.

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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90393cfb08190b5b45d3e5e32fad3 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f47209bd088190bf4c7687c0a5eed6 completed May 1, 2026, 9:27 a.m.
NEDg Description generation batch_69f47b7ac4048190ae09f18f1a90338f completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47db91f38819092b7b5c5e2bb489b completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.