Triple
T17520733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LIBSVM |
E426672
|
entity |
| Predicate | includesTool |
P1393
|
FINISHED |
| Object |
svm-scale
svm-scale is a utility program in the LIBSVM suite used to normalize and scale feature values in datasets before training support vector machine models.
|
E426672
|
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: svm-scale | Statement: [LIBSVM, includesTool, svm-scale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: svm-scale Context triple: [LIBSVM, includesTool, svm-scale]
-
A.
libsvm
libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
-
B.
Svm
Svm is the station code used to identify Svanemøllen railway station in Copenhagen’s public transport system.
-
C.
Support Vector Machines
Support Vector Machines are a class of supervised learning algorithms used primarily for classification and regression tasks, which work by finding the optimal separating hyperplane between data classes in a high-dimensional feature space.
-
D.
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.
-
E.
SVR
SVR is the set of post-nominal letters used to denote recipients of the Order of the White Rose of Finland.
- 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: svm-scale Triple: [LIBSVM, includesTool, svm-scale]
Generated description
svm-scale is a utility program in the LIBSVM suite used to normalize and scale feature values in datasets before training support vector machine models.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: svm-scale Target entity description: svm-scale is a utility program in the LIBSVM suite used to normalize and scale feature values in datasets before training support vector machine models.
-
A.
libsvm
chosen
libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
-
B.
Svm
Svm is the station code used to identify Svanemøllen railway station in Copenhagen’s public transport system.
-
C.
Support Vector Machines
Support Vector Machines are a class of supervised learning algorithms used primarily for classification and regression tasks, which work by finding the optimal separating hyperplane between data classes in a high-dimensional feature space.
-
D.
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.
-
E.
SVR
SVR is the set of post-nominal letters used to denote recipients of the Order of the White Rose of Finland.
- F. None of above.
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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d23cf08190925510344fa36f57 |
completed | April 19, 2026, 3:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01c94237d08190bb1f874735c87803 |
completed | May 11, 2026, 12:19 p.m. |
| NEDg | Description generation | batch_6a01cabea2b48190a690b17a88d45b40 |
completed | May 11, 2026, 12:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01cefa08f8819086cb86ce22193baa |
completed | May 11, 2026, 12:43 p.m. |
Created at: April 10, 2026, 5:49 a.m.