Triple
T18184244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tidyverse |
E435367
|
entity |
| Predicate | includesPackage |
P49317
|
FINISHED |
| Object |
dbplyr
dbplyr is an R package that translates dplyr code into SQL, enabling tidyverse-style data manipulation directly on databases.
|
E1311376
|
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: dbplyr | Statement: [tidyverse, includesPackage, dbplyr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: dbplyr Context triple: [tidyverse, includesPackage, dbplyr]
-
A.
dplyr
dplyr is a popular R package that provides a consistent, fast, and intuitive grammar of data manipulation for data frames and tibbles.
-
B.
BlazingSQL
BlazingSQL is an open-source SQL engine that enables GPU-accelerated data processing and analytics, often used within the NVIDIA RAPIDS ecosystem for high-performance query execution on large datasets.
-
C.
tidyverse
tidyverse is a collection of R packages designed for data science, emphasizing a consistent, human-readable grammar for data manipulation, visualization, and analysis.
-
D.
PL/Python
PL/Python is a procedural language extension for PostgreSQL that allows writing database functions and triggers in the Python programming language.
-
E.
Snowpark DataFrame API
The Snowpark DataFrame API is a developer framework for building and executing scalable, DataFrame-style data transformations and applications directly within the Snowflake data platform.
- 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: dbplyr Triple: [tidyverse, includesPackage, dbplyr]
Generated description
dbplyr is an R package that translates dplyr code into SQL, enabling tidyverse-style data manipulation directly on databases.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: dbplyr Target entity description: dbplyr is an R package that translates dplyr code into SQL, enabling tidyverse-style data manipulation directly on databases.
-
A.
dplyr
dplyr is a popular R package that provides a consistent, fast, and intuitive grammar of data manipulation for data frames and tibbles.
-
B.
BlazingSQL
BlazingSQL is an open-source SQL engine that enables GPU-accelerated data processing and analytics, often used within the NVIDIA RAPIDS ecosystem for high-performance query execution on large datasets.
-
C.
tidyverse
tidyverse is a collection of R packages designed for data science, emphasizing a consistent, human-readable grammar for data manipulation, visualization, and analysis.
-
D.
PL/Python
PL/Python is a procedural language extension for PostgreSQL that allows writing database functions and triggers in the Python programming language.
-
E.
Snowpark DataFrame API
The Snowpark DataFrame API is a developer framework for building and executing scalable, DataFrame-style data transformations and applications directly within the Snowflake data platform.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffd0abc81908cc07d28bdc3d48f |
completed | April 19, 2026, 2 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0398032e3081909455845718c73b78 |
completed | May 12, 2026, 9:13 p.m. |
| NEDg | Description generation | batch_6a03990a2bec8190b5d6a472bc9bb3fb |
completed | May 12, 2026, 9:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0399c98a88819090e579324d9423e5 |
completed | May 12, 2026, 9:21 p.m. |
Created at: April 10, 2026, 10:31 a.m.