Triple

T4371837
Position Surface form Disambiguated ID Type / Status
Subject R E98913 entity
Predicate hasPackage P14571 FINISHED
Object tidyr
tidyr is an R package that provides tools for reshaping and organizing data into tidy formats to facilitate analysis and visualization.
E436332 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: tidyr | Statement: [R, hasPackage, tidyr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: tidyr
Context triple: [R, hasPackage, tidyr]
  • A. pandas
    pandas is a popular open-source Python library that provides powerful, easy-to-use data structures and tools for data analysis and manipulation.
  • B. Tabularium
    The Tabularium was the official records office of ancient Rome, a monumental state archive building overlooking the Roman Forum.
  • C. Power Query
    Power Query is a data connection and transformation tool used to import, clean, and reshape data from various sources before analysis in Microsoft Power BI and other Microsoft products.
  • D. Quinta Normal
    Quinta Normal is a commune in Santiago, Chile, known for its urban residential character and proximity to the historic Quinta Normal Park and several cultural institutions.
  • E. ColumnTransformer
    ColumnTransformer is a scikit-learn utility that applies different preprocessing or transformation pipelines to specified columns of a dataset within a single unified estimator.
  • 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: tidyr
Triple: [R, hasPackage, tidyr]
Generated description
tidyr is an R package that provides tools for reshaping and organizing data into tidy formats to facilitate analysis and visualization.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: tidyr
Target entity description: tidyr is an R package that provides tools for reshaping and organizing data into tidy formats to facilitate analysis and visualization.
  • A. tidyverse
    tidyverse is a collection of R packages designed for data science, emphasizing a consistent, human-readable grammar for data manipulation, visualization, and analysis.
  • B. pandas
    pandas is a popular open-source Python library that provides powerful, easy-to-use data structures and tools for data analysis and manipulation.
  • C. Tabularium
    The Tabularium was the official records office of ancient Rome, a monumental state archive building overlooking the Roman Forum.
  • D. Power Query
    Power Query is a data connection and transformation tool used to import, clean, and reshape data from various sources before analysis in Microsoft Power BI and other Microsoft products.
  • E. Quinta Normal
    Quinta Normal is a commune in Santiago, Chile, known for its urban residential character and proximity to the historic Quinta Normal Park and several cultural institutions.
  • 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_69b3454db3708190aeafd814413c4c3d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3521dffbc8190b9300a7f4f64bdc0 completed March 12, 2026, 11:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e50bcc9481909b0b9d60198dce63 completed March 14, 2026, 10:45 p.m.
NEDg Description generation batch_69b5eeadd68881909820a75aaff9d8d5 completed March 14, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_69b5ef36f2bc8190a21e0f2fadbdd697 completed March 14, 2026, 11:28 p.m.
Created at: March 12, 2026, 11:17 p.m.