Triple

T3981856
Position Surface form Disambiguated ID Type / Status
Subject CREA corpus E85775 entity
Predicate acronym P43 FINISHED
Object CREA
CREA is a large reference corpus of contemporary Spanish used for linguistic research and language analysis.
E403329 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: CREA | Statement: [CREA corpus, acronym, CREA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CREA
Context triple: [CREA corpus, acronym, CREA]
  • A. CREI
    CREI is a Barcelona-based research institute specializing in macroeconomics and international economics, closely linked to academic institutions such as Universitat Pompeu Fabra.
  • B. Create
    Create is an American public television multicast network focused on how-to and lifestyle programming, including cooking, travel, home improvement, and crafts.
  • C. CREO Movement
    CREO Movement is an Ecuadorian political party associated with center-right, pro-market policies and the political career of former president Guillermo Lasso.
  • D. Universal Creative
    Universal Creative is the design and development division of Universal Parks & Resorts responsible for creating many of its iconic theme park attractions and experiences.
  • E. CREST
    CREST is the UK’s central securities depository and electronic settlement system used to hold and settle trades in shares and other securities.
  • 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: CREA
Triple: [CREA corpus, acronym, CREA]
Generated description
CREA is a large reference corpus of contemporary Spanish used for linguistic research and language analysis.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: CREA
Target entity description: CREA is a large reference corpus of contemporary Spanish used for linguistic research and language analysis.
  • A. CREI
    CREI is a Barcelona-based research institute specializing in macroeconomics and international economics, closely linked to academic institutions such as Universitat Pompeu Fabra.
  • B. Create
    Create is an American public television multicast network focused on how-to and lifestyle programming, including cooking, travel, home improvement, and crafts.
  • C. CREO Movement
    CREO Movement is an Ecuadorian political party associated with center-right, pro-market policies and the political career of former president Guillermo Lasso.
  • D. Universal Creative
    Universal Creative is the design and development division of Universal Parks & Resorts responsible for creating many of its iconic theme park attractions and experiences.
  • E. CREST
    CREST is the UK’s central securities depository and electronic settlement system used to hold and settle trades in shares and other securities.
  • 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_69aed93908348190a26c8aaf4fab3e86 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9db804c8190ad96656cb7b1a4fe completed March 9, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b540257c188190899b00bf1d0247d2 completed March 14, 2026, 11:01 a.m.
NEDg Description generation batch_69b54111e5188190ab8ec23124c22981 completed March 14, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69b54193105c81909e2a4e368aae36e8 completed March 14, 2026, 11:08 a.m.
Created at: March 9, 2026, 3:33 p.m.