See centroid in All languages combined, or Wiktionary
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"etymology_text": "From centre + -oid. From 1844, used as a replacement for the older terms \"centre of gravity\" and \"centre of mass\" in situations described in purely geometrical terms, and subsequently used for further generalisations.",
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"ref": "1892, Leander Miller Hoskins, The Elements of Graphic Statics, MacMillan and Co., pages 151–152:",
"text": "The center of gravity of any body or geometrical magnitude is by definition the same as the centroid of a certain system of parallel forces. It will be convenient, therefore, to use the word centroid in most cases instead of center of gravity.[…]The centroid of any area may be found by the following method: Divide the area into parts such that the area and centroid of each part are known. Take the centroids of the partial areas as the points of application of forces proportional respectively to those areas. The centroid of this system of forces is the centroid of the total area, and may be found by the method of Art. 172.",
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{
"ref": "2004, Richard L. Francis, Timothy J. Lowe, Arie Tamir, “7: Demand Point Aggregation for Local Models”, in Zvi Drezner, Horst W. Hamacher, editors, Facility Location: Applications and Theory, Springer-Verlag, page 207:",
"text": "For example, if a postal code area (PCA) has 1000 distinct residences, we might suppose all 1000 residences are at the centroid of the PCA. Centroids are commonly used, for example, with geographic information systems and CD-ROM phone books (Francis, Lowe, Rushton and Rayco 1999).",
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"ref": "2020, Cheng Zhang, Qiuchi Li, Lingyu Hua, Dawei Song, Assessing the Memory Ability of Recurrent Neural Networks, Giuseppe De Giacomo, et al. (editors), ECAI 2020: 24th European Conference on Artificial Intelligence, IOS Press, page 1660, In ℝⁿ, a centroid is the mean position of all the points in all of the coordinate directions. The centroid of a subset 𝒳 of ℝⁿ is computed as follows",
"text": "operatorname Centroid(𝒳)=(∫xg(x)dx)/(∫g(x)dx) (6)\nwhere the integrals are taken over the whole space ℝⁿ, and g is the characteristic function of the subset, which is 1 inside 𝒳 and 0 outside it [27]."
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"The point at which gravitational force (or other universally and uniformly acting force) may be supposed to act on a given rigid, uniformly dense body; the centre of gravity or centre of mass."
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"text": "The centroid of an arbitrary function f is given by #x5C;frac#x7B;#x5C;intxf(x)dx#x7D;#x7B;#x5C;intf(x)dx#x7D;, where the integrals are calculated over the domain of f.",
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"(mathematical analysis, of a function) An analogue of the centre of gravity of a nonuniform body in which local density is replaced by a specified function (which can take negative values) and the place of the body's shape is taken by the function's domain."
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"sense": "centre of gravity of a set of points of equal mass",
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"ref": "2011, Ross Maciejewski, Data Representations, Transformations, and Statistics for Visual Reasoning, Morgan & Claypool Publishers, page 34:",
"text": "The k-means procedure classifies a given data set by using a user defined number of clusters, k, a priori. The centroids can be placed randomly, or algorithmically, but it should be noted that the initial placement will affect the result. The next step is to analyze each point within the data set and group it with the nearest centroid according to some distance metric. When all points have been assigned to a group, a new centroid is calculated for each group as a barycenter of the cluster, resulting from the previous step. Once the k new centroids are calculated, the algorithm reiterates through the data set, and each sample is again assigned to a cluster based on its distance to the new centroids. This process is continued until the position^([sic]) of the centroids no longer change.",
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"ref": "2012, Biswanath Panda, Joshua S. Herbach, Sugato Basu, Roberto J. Bayardo, “2: MapReduce and its Application to Massively Parallel Learning of Decision Tree Ensembles”, in Ron Bekkerman, Mikhail Bilenko, John Langford, editors, Scaling Up Machine Learning, Cambridge University Press, page 26:",
"text": "The k-means clustering algorithm (MacQueen, 1967) is a widely used clustering method that applies relocation of points to find a locally optimal partitioning of a dataset. In k-means, the total distance between each data point and a representative point (centroid) of the cluster to which it is assigned is minimized. Each iteration of k-means has two steps. In the cluster assignment step, k-means assigns each point to a cluster such that, of all the current cluster centroids, the point is closest to the centroid of that cluster. In the cluster re-estimation step, k-means re-estimates the new cluster centroids based on the reassignments of points to clusters in the previous step. The cluster re-assignment and centroid re-estimation steps proceed in iterations until a specified convergence criterion is reached, such as when the total distance between clusters and centroids does not change substantially from one iteration to another.",
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"text": "1974 [Prentice-Hall], Narsingh Deo, Graph Theory with Applications to Engineering and Computer Science, 2017, Dover, page 248,\nJust as in the case of centers of a tree (Section 3-4), it can be shown that every tree has either one centroid or two centroids. It can also be shown that if a tree has two centroids, the centroids are adjacent."
},
{
"text": "2009, Hao Yuan, Patrick Eugster, An Efficient Algorithm for Solving the Dyck-CFL Reachability Problem on Trees, Giuseppe Castagna (editor), Programming Languages and Systems: 18th European Symposium, Proceedings, Springer, LNCS 5502, page 186,\nA node x in a tree T is called a centroid of T if the removal of x will make the size of each remaining connected component no greater than |T|/2. A tree may have at most two centroids, and if there are two then one must be a neighbor of the other [6, 5]. Throughout this paper, we specify the centroid to be the one whose numbering is lexicographically smaller (i.e, we number the nodes from 1 to n). There exists a linear time algorithm to compute the centroid of a tree due to the work of Goldman [21]. We use operatorname CT(T) to denote the centroid of T computed by the linear time algorithm."
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"(graph theory, of a tree) Given a tree of n nodes, either (1) a unique node whose removal would split the tree into subtrees of fewer than n/2 nodes, or (2) either of a pair of adjacent nodes such that removal of the edge connecting them would split the tree into two subtrees of exactly n/2 nodes."
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"_dis1": "26 10 13 30 15 6",
"code": "cmn",
"lang": "Chinese Mandarin",
"roman": "xíngxīn",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "形心"
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"code": "fi",
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"word": "painopiste"
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"code": "fr",
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"word": "centroïde"
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"word": "centroido"
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"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
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"masculine"
],
"word": "meánlár"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "it",
"lang": "Italian",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "centroide"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "ko",
"lang": "Korean",
"roman": "dosim",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "도심"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "ko",
"lang": "Korean",
"roman": "moyangjungsim",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "모양중심"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "pt",
"lang": "Portuguese",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "centroide"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "ru",
"lang": "Russian",
"roman": "centróid",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "центро́ид"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "ru",
"lang": "Russian",
"roman": "baricéntr",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "барице́нтр"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "ru",
"lang": "Russian",
"roman": "centr tjážesti",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "центр тя́жести"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "es",
"lang": "Spanish",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "centroide"
},
{
"_dis1": "26 10 13 30 15 6",
"code": "vi",
"lang": "Vietnamese",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "trọng tâm"
}
],
"wikipedia": [
"centroid"
],
"word": "centroid"
}
{
"categories": [
"English countable nouns",
"English entries with incorrect language header",
"English lemmas",
"English nouns",
"English terms suffixed with -oid",
"Entries with translation boxes",
"Pages with 1 entry",
"Pages with entries",
"Requests for review of German translations",
"Terms with Finnish translations",
"Terms with French translations",
"Terms with German translations",
"Terms with Ido translations",
"Terms with Irish translations",
"Terms with Italian translations",
"Terms with Korean translations",
"Terms with Mandarin translations",
"Terms with Portuguese translations",
"Terms with Russian translations",
"Terms with Spanish translations",
"Terms with Vietnamese translations"
],
"derived": [
{
"word": "bicentroidal"
},
{
"word": "centroidal"
},
{
"word": "centroided"
},
{
"word": "centroider"
},
{
"word": "centroiding"
},
{
"word": "function centroid"
},
{
"word": "geometric centroid"
},
{
"word": "gyrocentroid"
},
{
"word": "intercentroid"
},
{
"word": "quasicentroid"
}
],
"etymology_templates": [
{
"args": {
"1": "en",
"2": "centre",
"3": "-oid"
},
"expansion": "centre + -oid",
"name": "affix"
}
],
"etymology_text": "From centre + -oid. From 1844, used as a replacement for the older terms \"centre of gravity\" and \"centre of mass\" in situations described in purely geometrical terms, and subsequently used for further generalisations.",
"forms": [
{
"form": "centroids",
"tags": [
"plural"
]
}
],
"head_templates": [
{
"args": {},
"expansion": "centroid (plural centroids)",
"name": "en-noun"
}
],
"lang": "English",
"lang_code": "en",
"pos": "noun",
"related": [
{
"word": "barycentre"
},
{
"word": "barycenter"
},
{
"word": "geographical centre"
}
],
"senses": [
{
"categories": [
"English terms with quotations",
"Quotation templates to be cleaned",
"en:Engineering",
"en:Geometry",
"en:Physics"
],
"examples": [
{
"ref": "1892, Leander Miller Hoskins, The Elements of Graphic Statics, MacMillan and Co., pages 151–152:",
"text": "The center of gravity of any body or geometrical magnitude is by definition the same as the centroid of a certain system of parallel forces. It will be convenient, therefore, to use the word centroid in most cases instead of center of gravity.[…]The centroid of any area may be found by the following method: Divide the area into parts such that the area and centroid of each part are known. Take the centroids of the partial areas as the points of application of forces proportional respectively to those areas. The centroid of this system of forces is the centroid of the total area, and may be found by the method of Art. 172.",
"type": "quote"
},
{
"ref": "2004, Richard L. Francis, Timothy J. Lowe, Arie Tamir, “7: Demand Point Aggregation for Local Models”, in Zvi Drezner, Horst W. Hamacher, editors, Facility Location: Applications and Theory, Springer-Verlag, page 207:",
"text": "For example, if a postal code area (PCA) has 1000 distinct residences, we might suppose all 1000 residences are at the centroid of the PCA. Centroids are commonly used, for example, with geographic information systems and CD-ROM phone books (Francis, Lowe, Rushton and Rayco 1999).",
"type": "quote"
},
{
"ref": "2020, Cheng Zhang, Qiuchi Li, Lingyu Hua, Dawei Song, Assessing the Memory Ability of Recurrent Neural Networks, Giuseppe De Giacomo, et al. (editors), ECAI 2020: 24th European Conference on Artificial Intelligence, IOS Press, page 1660, In ℝⁿ, a centroid is the mean position of all the points in all of the coordinate directions. The centroid of a subset 𝒳 of ℝⁿ is computed as follows",
"text": "operatorname Centroid(𝒳)=(∫xg(x)dx)/(∫g(x)dx) (6)\nwhere the integrals are taken over the whole space ℝⁿ, and g is the characteristic function of the subset, which is 1 inside 𝒳 and 0 outside it [27]."
}
],
"glosses": [
"The point at which gravitational force (or other universally and uniformly acting force) may be supposed to act on a given rigid, uniformly dense body; the centre of gravity or centre of mass."
],
"links": [
[
"geometry",
"geometry"
],
[
"physics",
"physics"
],
[
"engineering",
"engineering#Noun"
],
[
"centre of gravity",
"centre of gravity"
],
[
"centre of mass",
"centre of mass"
]
],
"raw_glosses": [
"(geometry, physics, engineering, of an object or a geometrical figure) The point at which gravitational force (or other universally and uniformly acting force) may be supposed to act on a given rigid, uniformly dense body; the centre of gravity or centre of mass."
],
"raw_tags": [
"of an object or a geometrical figure"
],
"topics": [
"engineering",
"geometry",
"mathematics",
"natural-sciences",
"physical-sciences",
"physics",
"sciences"
]
},
{
"categories": [
"en:Geometry"
],
"glosses": [
"The point of intersection of the three medians of a given triangle; the point whose (Cartesian) coordinates are the arithmetic mean of the coordinates of the three vertices."
],
"links": [
[
"geometry",
"geometry"
],
[
"intersection",
"intersection"
],
[
"median",
"median"
],
[
"arithmetic mean",
"arithmetic mean"
]
],
"raw_glosses": [
"(geometry, specifically, of a triangle) The point of intersection of the three medians of a given triangle; the point whose (Cartesian) coordinates are the arithmetic mean of the coordinates of the three vertices."
],
"raw_tags": [
"of a triangle"
],
"tags": [
"specifically"
],
"topics": [
"geometry",
"mathematics",
"sciences"
]
},
{
"glosses": [
"the point whose (Cartesian) coordinates are the arithmetic mean of the coordinates of a given finite set of points."
],
"links": [
[
"arithmetic mean",
"arithmetic mean"
]
],
"raw_glosses": [
"(of a finite set of points) the point whose (Cartesian) coordinates are the arithmetic mean of the coordinates of a given finite set of points."
],
"raw_tags": [
"of a finite set of points"
]
},
{
"categories": [
"English terms with usage examples",
"en:Mathematical analysis"
],
"examples": [
{
"text": "The centroid of an arbitrary function f is given by #x5C;frac#x7B;#x5C;intxf(x)dx#x7D;#x7B;#x5C;intf(x)dx#x7D;, where the integrals are calculated over the domain of f.",
"type": "example"
}
],
"glosses": [
"An analogue of the centre of gravity of a nonuniform body in which local density is replaced by a specified function (which can take negative values) and the place of the body's shape is taken by the function's domain."
],
"links": [
[
"mathematical analysis",
"mathematical analysis"
],
[
"centre of gravity",
"centre of gravity"
],
[
"domain",
"domain"
]
],
"raw_glosses": [
"(mathematical analysis, of a function) An analogue of the centre of gravity of a nonuniform body in which local density is replaced by a specified function (which can take negative values) and the place of the body's shape is taken by the function's domain."
],
"raw_tags": [
"of a function"
],
"topics": [
"mathematical-analysis",
"mathematics",
"sciences"
]
},
{
"categories": [
"English terms with quotations",
"en:Statistics"
],
"examples": [
{
"ref": "2011, Ross Maciejewski, Data Representations, Transformations, and Statistics for Visual Reasoning, Morgan & Claypool Publishers, page 34:",
"text": "The k-means procedure classifies a given data set by using a user defined number of clusters, k, a priori. The centroids can be placed randomly, or algorithmically, but it should be noted that the initial placement will affect the result. The next step is to analyze each point within the data set and group it with the nearest centroid according to some distance metric. When all points have been assigned to a group, a new centroid is calculated for each group as a barycenter of the cluster, resulting from the previous step. Once the k new centroids are calculated, the algorithm reiterates through the data set, and each sample is again assigned to a cluster based on its distance to the new centroids. This process is continued until the position^([sic]) of the centroids no longer change.",
"type": "quote"
},
{
"ref": "2012, Biswanath Panda, Joshua S. Herbach, Sugato Basu, Roberto J. Bayardo, “2: MapReduce and its Application to Massively Parallel Learning of Decision Tree Ensembles”, in Ron Bekkerman, Mikhail Bilenko, John Langford, editors, Scaling Up Machine Learning, Cambridge University Press, page 26:",
"text": "The k-means clustering algorithm (MacQueen, 1967) is a widely used clustering method that applies relocation of points to find a locally optimal partitioning of a dataset. In k-means, the total distance between each data point and a representative point (centroid) of the cluster to which it is assigned is minimized. Each iteration of k-means has two steps. In the cluster assignment step, k-means assigns each point to a cluster such that, of all the current cluster centroids, the point is closest to the centroid of that cluster. In the cluster re-estimation step, k-means re-estimates the new cluster centroids based on the reassignments of points to clusters in the previous step. The cluster re-assignment and centroid re-estimation steps proceed in iterations until a specified convergence criterion is reached, such as when the total distance between clusters and centroids does not change substantially from one iteration to another.",
"type": "quote"
}
],
"glosses": [
"the arithmetic mean (alternatively, median) position of a cluster of points in a coordinate system based on some application-dependent measure of distance."
],
"links": [
[
"statistics",
"statistics"
],
[
"cluster",
"cluster"
],
[
"arithmetic mean",
"arithmetic mean"
],
[
"median",
"median"
]
],
"qualifier": "cluster analysis",
"raw_glosses": [
"(statistics, cluster analysis, of a cluster of points) the arithmetic mean (alternatively, median) position of a cluster of points in a coordinate system based on some application-dependent measure of distance."
],
"raw_tags": [
"of a cluster of points"
],
"topics": [
"mathematics",
"sciences",
"statistics"
]
},
{
"categories": [
"en:Graph theory"
],
"examples": [
{
"text": "1974 [Prentice-Hall], Narsingh Deo, Graph Theory with Applications to Engineering and Computer Science, 2017, Dover, page 248,\nJust as in the case of centers of a tree (Section 3-4), it can be shown that every tree has either one centroid or two centroids. It can also be shown that if a tree has two centroids, the centroids are adjacent."
},
{
"text": "2009, Hao Yuan, Patrick Eugster, An Efficient Algorithm for Solving the Dyck-CFL Reachability Problem on Trees, Giuseppe Castagna (editor), Programming Languages and Systems: 18th European Symposium, Proceedings, Springer, LNCS 5502, page 186,\nA node x in a tree T is called a centroid of T if the removal of x will make the size of each remaining connected component no greater than |T|/2. A tree may have at most two centroids, and if there are two then one must be a neighbor of the other [6, 5]. Throughout this paper, we specify the centroid to be the one whose numbering is lexicographically smaller (i.e, we number the nodes from 1 to n). There exists a linear time algorithm to compute the centroid of a tree due to the work of Goldman [21]. We use operatorname CT(T) to denote the centroid of T computed by the linear time algorithm."
}
],
"glosses": [
"Given a tree of n nodes, either (1) a unique node whose removal would split the tree into subtrees of fewer than n/2 nodes, or (2) either of a pair of adjacent nodes such that removal of the edge connecting them would split the tree into two subtrees of exactly n/2 nodes."
],
"links": [
[
"graph theory",
"graph theory"
],
[
"tree",
"tree"
],
[
"node",
"node"
]
],
"raw_glosses": [
"(graph theory, of a tree) Given a tree of n nodes, either (1) a unique node whose removal would split the tree into subtrees of fewer than n/2 nodes, or (2) either of a pair of adjacent nodes such that removal of the edge connecting them would split the tree into two subtrees of exactly n/2 nodes."
],
"raw_tags": [
"of a tree"
],
"topics": [
"graph-theory",
"mathematics",
"sciences"
]
}
],
"sounds": [
{
"audio": "LL-Q1860 (eng)-Flame, not lame-centroid.wav",
"mp3_url": "https://upload.wikimedia.org/wikipedia/commons/transcoded/a/a1/LL-Q1860_%28eng%29-Flame%2C_not_lame-centroid.wav/LL-Q1860_%28eng%29-Flame%2C_not_lame-centroid.wav.mp3",
"ogg_url": "https://upload.wikimedia.org/wikipedia/commons/transcoded/a/a1/LL-Q1860_%28eng%29-Flame%2C_not_lame-centroid.wav/LL-Q1860_%28eng%29-Flame%2C_not_lame-centroid.wav.ogg"
}
],
"synonyms": [
{
"sense": "centre of gravity of a uniform, rigid object",
"word": "barycentre"
},
{
"sense": "centre of gravity of a uniform, rigid object",
"word": "centre of area"
},
{
"sense": "centre of gravity of a uniform, rigid object",
"word": "centre of gravity"
},
{
"sense": "centre of gravity of a uniform, rigid object",
"word": "centre of mass"
},
{
"sense": "centre of gravity of a uniform, rigid object",
"word": "centre of volume"
},
{
"sense": "centre of gravity of a uniform, rigid object",
"word": "geometric centre"
},
{
"sense": "centre of gravity of a uniform, rigid object",
"word": "geometric centroid"
},
{
"sense": "centre of gravity of a set of points of equal mass",
"word": "barycentre"
},
{
"sense": "centre of gravity of a set of points of equal mass",
"word": "centre of gravity"
},
{
"sense": "centre of gravity of a set of points of equal mass",
"word": "centre of mass"
},
{
"sense": "centroid of a function",
"word": "function centroid"
},
{
"sense": "graph theory: type of node in a tree",
"word": "tree centroid"
}
],
"translations": [
{
"code": "cmn",
"lang": "Chinese Mandarin",
"roman": "xíngxīn",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "形心"
},
{
"code": "fi",
"lang": "Finnish",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "painopiste"
},
{
"code": "fr",
"lang": "French",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "centroïde"
},
{
"code": "io",
"lang": "Ido",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "centroido"
},
{
"code": "ga",
"lang": "Irish",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "meánlár"
},
{
"code": "it",
"lang": "Italian",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "centroide"
},
{
"code": "ko",
"lang": "Korean",
"roman": "dosim",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "도심"
},
{
"code": "ko",
"lang": "Korean",
"roman": "moyangjungsim",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "모양중심"
},
{
"code": "pt",
"lang": "Portuguese",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "centroide"
},
{
"code": "ru",
"lang": "Russian",
"roman": "centróid",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "центро́ид"
},
{
"code": "ru",
"lang": "Russian",
"roman": "baricéntr",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "барице́нтр"
},
{
"code": "ru",
"lang": "Russian",
"roman": "centr tjážesti",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "центр тя́жести"
},
{
"code": "es",
"lang": "Spanish",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"tags": [
"masculine"
],
"word": "centroide"
},
{
"code": "vi",
"lang": "Vietnamese",
"sense": "mean position of points in a geometrical figure — see also center of gravity, barycenter",
"word": "trọng tâm"
}
],
"wikipedia": [
"centroid"
],
"word": "centroid"
}
Download raw JSONL data for centroid meaning in English (15.5kB)
This page is a part of the kaikki.org machine-readable English dictionary. This dictionary is based on structured data extracted on 2024-12-21 from the enwiktionary dump dated 2024-12-04 using wiktextract (d8cb2f3 and 4e554ae). The data shown on this site has been post-processed and various details (e.g., extra categories) removed, some information disambiguated, and additional data merged from other sources. See the raw data download page for the unprocessed wiktextract data.
If you use this data in academic research, please cite Tatu Ylonen: Wiktextract: Wiktionary as Machine-Readable Structured Data, Proceedings of the 13th Conference on Language Resources and Evaluation (LREC), pp. 1317-1325, Marseille, 20-25 June 2022. Linking to the relevant page(s) under https://kaikki.org would also be greatly appreciated.