Triple
T18222408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R Language Definition |
E436336
|
entity |
| Predicate | maintainedBy |
P86
|
FINISHED |
| Object | R Core Team |
—
|
NE NERFINISHED |
How this triple was built (2 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: R Core Team | Statement: [R Language Definition, maintainedBy, R Core Team]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R Core Team Context triple: [R Language Definition, maintainedBy, R Core Team]
-
A.
R Core Team
chosen
R Core Team is the group of developers responsible for maintaining and advancing the R programming language and its core infrastructure.
-
B.
Ross Ihaka
Ross Ihaka is a New Zealand statistician best known as one of the original creators of the R programming language.
-
C.
Hadley Wickham
Hadley Wickham is a prominent statistician and software developer best known for creating many of the core R packages in the tidyverse, which have transformed data analysis and visualization in R.
-
D.
RSpec core team
The RSpec core team is the group of maintainers responsible for developing and overseeing the core components of the RSpec testing framework for Ruby.
-
E.
Pandas Developers
Pandas Developers are the community of programmers and contributors who maintain and advance the pandas Python library for data analysis and manipulation.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e47c85108190bd9707b40bdfdb38 |
completed | April 19, 2026, 2:19 p.m. |
Created at: April 10, 2026, 10:32 a.m.