Skip to content
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.gitignore
README.md
clics3-network.gml.zip
clics3.sqlite.zip
datasets.md
datasets.txt
languoids.geojson
requirements.txt

README.md

CLICS³

The third installment of CLICS - the database of Cross-Linguistic Colexifications.

Cite as

Rzymski, Tresoldi et al. 2019. The Database of Cross-Linguistic Colexifications, reproducible analysis of cross- linguistic polysemies. DOI: doi.org/10.17613/5awv-6w15

This repository contains

This data is licensed under CC BY 4.0.

Creating the CLICS database

  1. Install version 3 of the Python package pyclics DOI:
    pip install "pyclics>=3.0"
  2. Download and install the Lexibank datasets from which to aggregate colexifications:
    pip install -r datasets.txt
  3. Download data for the reference catalogs Glottolog and Concepticon:
    cldfbench catconfig
  4. Create the SQLite database clics.sqlite:
    clics load --glottolog-version v4.0 --concepticon-version v2.2.0
    and confirm all 30 datasets have been loaded
    clics datasets
# Dataset Parameters Concepticon Varieties Glottocodes Families
1 abrahammonpa 304 304 30 16 2
2 allenbai 499 499 9 9 1
3 bantubvd 420 415 10 10 1
4 beidasinitic 736 735 18 18 1
5 bodtkhobwa 553 536 8 8 1
6 bowernpny 338 338 175 172 1
7 castrosui 510 508 16 3 1
8 chenhmongmien 793 793 22 20 1
9 diacl 537 537 371 351 25
10 halenepal 699 662 13 13 2
11 hantganbangime 299 299 22 22 5
12 hubercolumbian 346 345 69 65 16
13 ids 1310 1308 320 275 60
14 kraftchadic 433 428 66 59 2
15 lexirumah 604 602 357 231 12
16 logos 707 707 5 5 1
17 marrisonnaga 580 572 40 39 1
18 mitterhoferbena 342 335 13 13 1
19 naganorgyalrongic 969 877 10 8 1
20 northeuralex 952 951 107 107 21
21 robinsonap 391 391 13 13 1
22 satterthwaitetb 418 418 18 18 1
23 sohartmannchin 279 279 8 7 1
24 suntb 929 929 49 49 1
25 tls 1140 811 126 107 1
26 transnewguineaorg 904 865 1004 760 106
27 tryonsolomon 317 314 111 96 5
28 wold 1459 1458 41 41 24
29 yanglalo 875 869 7 7 1
30 zgraggenmadang 311 310 98 98 1
TOTAL 0 2906 3156 2271 200
  1. Create the colexification network (encoded as GML graph):
    clics -t 3 -f families colexification --show 20 --format pipe
    This will create the graph at graphs/network-3-families.gml and show the 20 most common colexifications:
ID A Concept A ID B Concept B Families Languages Words
906 TREE 1803 WOOD 59 348 361
1313 MOON 1370 MONTH 57 324 327
72 CLAW 1258 FINGERNAIL 55 236 243
1297 LEG 1301 FOOT 52 349 358
1352 KNIFE 3210 KNIFE (FOR EATING) 51 268 282
2267 SON-IN-LAW (OF MAN) 2266 SON-IN-LAW (OF WOMAN) 49 261 280
763 SKIN 1204 BARK 49 209 213
1307 LANGUAGE 1599 WORD 49 148 149
1277 HAND 1673 ARM 48 294 300
1408 HEAR 1608 LISTEN 48 107 109
634 MEAT 2259 FLESH 47 252 262
2265 DAUGHTER-IN-LAW (OF MAN) 2264 DAUGHTER-IN-LAW (OF WOMAN) 47 234 256
763 SKIN 629 LEATHER 46 236 258
837 BLUE 1425 GREEN 46 195 204
2261 MALE (OF PERSON) 2263 MALE (OF ANIMAL) 45 145 163
1199 WIFE 962 WOMAN 44 289 301
480 PLATE 481 DISH 44 155 170
2260 FEMALE (OF PERSON) 2262 FEMALE (OF ANIMAL) 44 146 154
1228 EARTH (SOIL) 626 LAND 43 159 167
667 ROAD 2252 PATH 43 133 153
705 GO UP (ASCEND) 1102 CLIMB 43 132 146
683 PERSON 1554 MAN 41 199 205
2255 FATHER-IN-LAW (OF MAN) 2254 FATHER-IN-LAW (OF WOMAN) 41 187 204
133 WEAVE 3294 BRAID (VERB) OR WEAVE (BASKET) 41 122 133
2261 MALE (OF PERSON) 1554 MAN 41 104 115
1474 SEA 645 OCEAN 41 101 110
215 LIE DOWN 1585 SLEEP 40 191 197
1265 HIGH 711 TALL 40 168 182
256 FOOD 1526 MEAL 40 124 136
1732 SKY 1565 HEAVEN 40 117 120
1443 WALK 695 GO 39 288 320
2257 MOTHER-IN-LAW (OF MAN) 2256 MOTHER-IN-LAW (OF WOMAN) 39 181 203
1618 GRANDSON 1619 GRANDDAUGHTER 39 133 151
1203 LONG 711 TALL 39 113 121
2260 FEMALE (OF PERSON) 962 WOMAN 39 109 119
948 WATER 666 RIVER 38 197 200
1229 OLD 406 OLD MAN 38 103 107
531 HOW MUCH 3450 HOW MANY PIECES 37 184 203
706 DARK 163 BLACK 37 95 97
855 SEIZE 702 CATCH 36 150 161
  1. Run subgraph and infomap cluster algorithms:
    clics --seed 42 -t 3 -f families makeapp
    The clustered networks will be written to GML graphs and exported in a way suitable for exploring with the CLICS javascript app. We can get some summary statistics running
    clics -t 3 -f families --graphname infomap graph_stats
    -----------  ----
    nodes        1647
    edges        2967
    components     92
    communities   249
    -----------  ----
  2. Finally, we can explore the clusters in the CLICS javascript app:
    clics runapp
You can’t perform that action at this time.