Triple
T4371820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R |
E98913
|
entity |
| Predicate | maintainedBy |
P86
|
FINISHED |
| Object | R Core Team |
E426690
|
NE FINISHED |
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, maintainedBy, R Core Team]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R Core Team Context triple: [R, 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.
R Foundation for Statistical Computing
The R Foundation for Statistical Computing is a non-profit organization that supports the development, maintenance, and promotion of the R programming language and its ecosystem.
-
C.
CRAN
CRAN is the Comprehensive R Archive Network, a primary repository for R packages, source code, and documentation used by the R programming community.
-
D.
Statistical Research Group at Columbia University
The Statistical Research Group at Columbia University was a World War II-era interdisciplinary team of statisticians and mathematicians that developed pioneering statistical methods for military operations and decision-making.
-
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 (3 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. |
Created at: March 12, 2026, 11:17 p.m.