Triple
T148132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python |
E3372
|
entity |
| Predicate | machineLearningLibrary |
P7265
|
FINISHED |
| Object |
scikit-learn
scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.
|
E17661
|
NE FINISHED |
How this triple was built (5 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: scikit-learn | Statement: [Python, machineLearningLibrary, scikit-learn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: scikit-learn Context triple: [Python, machineLearningLibrary, scikit-learn]
-
A.
Lifelong Learning Machines program
The Lifelong Learning Machines program is a DARPA research initiative aimed at developing AI systems that can continuously learn and adapt from experience in dynamic, real-world environments.
-
B.
Machine Learning Department, Carnegie Mellon University
The Machine Learning Department at Carnegie Mellon University is a pioneering academic unit dedicated to research and education in machine learning, artificial intelligence, and related computational disciplines.
-
C.
Boltzmann machines
Boltzmann machines are stochastic recurrent neural networks used for learning complex probability distributions, foundational in unsupervised learning and energy-based models.
-
D.
ROC
ROC is the commonly used abbreviation for the Royal Observer Corps, a former British civil defense organization that monitored aircraft and nuclear explosions during the 20th century.
-
E.
Open Data Lab
Open Data Lab is a World Wide Web Foundation initiative that supports the use of open data to drive social impact, innovation, and better governance, particularly in developing countries.
- 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: scikit-learn Triple: [Python, machineLearningLibrary, scikit-learn]
Generated description
scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: scikit-learn Target entity description: scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.
-
A.
Lifelong Learning Machines program
The Lifelong Learning Machines program is a DARPA research initiative aimed at developing AI systems that can continuously learn and adapt from experience in dynamic, real-world environments.
-
B.
Machine Learning Department, Carnegie Mellon University
The Machine Learning Department at Carnegie Mellon University is a pioneering academic unit dedicated to research and education in machine learning, artificial intelligence, and related computational disciplines.
-
C.
Boltzmann machines
Boltzmann machines are stochastic recurrent neural networks used for learning complex probability distributions, foundational in unsupervised learning and energy-based models.
-
D.
ROC
ROC is the commonly used abbreviation for the Royal Observer Corps, a former British civil defense organization that monitored aircraft and nuclear explosions during the 20th century.
-
E.
Open Data Lab
Open Data Lab is a World Wide Web Foundation initiative that supports the use of open data to drive social impact, innovation, and better governance, particularly in developing countries.
- F. None of above. chosen
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: machineLearningLibrary Context triple: [Python, machineLearningLibrary, scikit-learn]
-
A.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
B.
isMainLibraryOf
Indicates that a library serves as the primary or central library for a given organization, system, or collection.
-
C.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
D.
commonlyImplementedBy
Indicates that the referenced item (e.g., a standard, interface, or pattern) is frequently realized or put into practice by the associated implementing entities.
-
E.
computes
Indicates that one entity performs a calculation or processing operation to produce a result from given data or inputs.
- F. None of above. chosen
Provenance (7 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2c27754a881908ef5a96e05e515e3 |
completed | Feb. 28, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69a2c37177348190857d52872e6ab393 |
completed | Feb. 28, 2026, 10:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2c3c512f08190bb87f874524b1616 |
completed | Feb. 28, 2026, 10:30 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2587e598c81909e1082b813971f48 |
completed | Feb. 28, 2026, 2:52 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.