1.0.5

We have generated datasets using A Brief History of Human Time project.
These datasets contain different sets of seed nodes, categorized by various human arts and professions.

dataset (variant, size, None/train/val/test)	#roots	#smmaries	#nodes	#edges	#labels	roots category distribution	Running Time(sec)
WikiLitArt-s csv, graphml, croissant.json	494	10416	85346	136950	547	actor=150 composer=35 film=41 novelist=24 painter=59 poet=39 screenwriter=17 singer=72 writer=57	91.934
WikiLitArt-s-train csv, graphml, croissant.json	346	7234	61885	96497	508	actor=105 composer=24 film=29 novelist=17 painter=42 poet=27 screenwriter=12 singer=50 writer=40	66.023
WikiLitArt-s-val csv, graphml, croissant.json	74	1572	14763	20795	340	actor=23 composer=5 film=6 novelist=4 painter=9 poet=6 screenwriter=2 singer=11 writer=8	14.364
WikiLitArt-s-test csv, graphml, croissant.json	74	1626	15861	22029	350	actor=22 composer=6 film=6 novelist=3 painter=8 poet=6 screenwriter=3 singer=11 writer=9	14.6
WikiLitArt-m csv, graphml, croissant.json	494	10416	128061	220263	604	actor=150 composer=35 film=41 novelist=24 painter=59 poet=39 screenwriter=17 singer=72 writer=57	155.368
WikiLitArt-m-train csv, graphml, croissant.json	346	7234	93251	155667	566	actor=105 composer=24 film=29 novelist=17 painter=42 poet=27 screenwriter=12 singer=50 writer=40	111.636
WikiLitArt-m-val csv, graphml, croissant.json	74	1572	22214	33547	375	actor=23 composer=5 film=6 novelist=4 painter=9 poet=6 screenwriter=2 singer=11 writer=8	22.957
WikiLitArt-m-test csv, graphml, croissant.json	74	1626	24130	35980	394	actor=22 composer=6 film=6 novelist=3 painter=8 poet=6 screenwriter=3 singer=11 writer=9	26.187
WikiLitArt-l csv, graphml, croissant.json	494	10416	239491	466905	703	actor=150 composer=35 film=41 novelist=24 painter=59 poet=39 screenwriter=17 singer=72 writer=57	353.113
WikiLitArt-l-train csv, graphml, croissant.json	346	7234	176057	332279	661	actor=105 composer=24 film=29 novelist=17 painter=42 poet=27 screenwriter=12 singer=50 writer=40	244.544
WikiLitArt-l-val csv, graphml, croissant.json	74	1572	42745	71734	446	actor=23 composer=5 film=6 novelist=4 painter=9 poet=6 screenwriter=2 singer=11 writer=8	57.263
WikiLitArt-l-test csv, graphml, croissant.json	74	1626	46890	77931	493	actor=22 composer=6 film=6 novelist=3 painter=8 poet=6 screenwriter=3 singer=11 writer=9	60.466
WikiCinema-s csv, graphml, croissant.json	493	11750	70753	126915	469	actor=405 film=88	118.014
WikiCinema-s-train csv, graphml, croissant.json	345	8374	52712	89306	437	actor=284 film=61	84.364
WikiCinema-s-val csv, graphml, croissant.json	73	1650	13362	19280	305	actor=59 film=14	18.651
WikiCinema-s-test csv, graphml, croissant.json	75	1744	14777	21567	313	actor=62 film=13	19.851
WikiCinema-m csv, graphml, croissant.json	493	11750	101529	196061	541	actor=405 film=88	196.413
WikiCinema-m-train csv, graphml, croissant.json	345	8374	75900	138897	491	actor=284 film=61	142.091
WikiCinema-m-val csv, graphml, croissant.json	73	1650	19674	30152	344	actor=59 film=14	31.722
WikiCinema-m-test csv, graphml, croissant.json	75	1744	22102	34499	342	actor=62 film=13	33.674
WikiCinema-l csv, graphml, croissant.json	493	11750	185098	397546	614	actor=405 film=88	475.679
WikiCinema-l-train csv, graphml, croissant.json	345	8374	139598	284417	575	actor=284 film=61	333.148
WikiCinema-l-val csv, graphml, croissant.json	73	1650	37352	63744	412	actor=59 film=14	68.62
WikiCinema-l-test csv, graphml, croissant.json	75	1744	43238	74205	426	actor=62 film=13	87.07
WikiPro-s csv, graphml, croissant.json	493	9853	79825	125912	616	actor=58 football=156 journalist=14 lawyer=16 painter=23 player=25 politician=125 singer=27 sport=21 writer=28	126.119
WikiPro-s-train csv, graphml, croissant.json	345	6832	57529	87768	575	actor=41 football=109 journalist=10 lawyer=11 painter=16 player=17 politician=87 singer=19 sport=15 writer=20	89.874
WikiPro-s-val csv, graphml, croissant.json	74	1548	15769	21351	405	actor=9 football=23 journalist=2 lawyer=3 painter=3 player=4 politician=19 singer=4 sport=3 writer=4	21.021
WikiPro-s-test csv, graphml, croissant.json	74	1484	15657	21145	384	actor=8 football=24 journalist=2 lawyer=2 painter=4 player=4 politician=19 singer=4 sport=3 writer=4	21.743
WikiPro-m csv, graphml, croissant.json	493	9853	119305	198663	670	actor=58 football=156 journalist=14 lawyer=16 painter=23 player=25 politician=125 singer=27 sport=21 writer=28	208.157
WikiPro-m-train csv, graphml, croissant.json	345	6832	86434	138676	633	actor=41 football=109 journalist=10 lawyer=11 painter=16 player=17 politician=87 singer=19 sport=15 writer=20	141.563
WikiPro-m-val csv, graphml, croissant.json	74	1548	24230	34636	463	actor=9 football=23 journalist=2 lawyer=3 painter=3 player=4 politician=19 singer=4 sport=3 writer=4	36.045
WikiPro-m-test csv, graphml, croissant.json	74	1484	24117	34157	462	actor=8 football=24 journalist=2 lawyer=2 painter=4 player=4 politician=19 singer=4 sport=3 writer=4	36.967
WikiPro-l csv, graphml, croissant.json	493	9853	230442	412766	769	actor=58 football=156 journalist=14 lawyer=16 painter=23 player=25 politician=125 singer=27 sport=21 writer=28	489.409
WikiPro-l-train csv, graphml, croissant.json	345	6832	166685	290069	725	actor=41 football=109 journalist=10 lawyer=11 painter=16 player=17 politician=87 singer=19 sport=15 writer=20	334.864
WikiPro-l-val csv, graphml, croissant.json	74	1548	48205	74387	549	actor=9 football=23 journalist=2 lawyer=3 painter=3 player=4 politician=19 singer=4 sport=3 writer=4	84.089
WikiPro-l-test csv, graphml, croissant.json	74	1484	47981	72845	546	actor=8 football=24 journalist=2 lawyer=2 painter=4 player=4 politician=19 singer=4 sport=3 writer=4	92.545
WikiProFem-s csv, graphml, croissant.json	468	8338	79926	123193	571	actor=141 athletic=25 football=24 journalist=16 painter=16 player=32 politician=81 singer=69 sport=18 writer=46	177.63
WikiProFem-s-train csv, graphml, croissant.json	330	5587	58329	87492	521	actor=98 athletic=18 football=17 journalist=9 painter=13 player=22 politician=57 singer=48 sport=14 writer=34	127.614
WikiProFem-s-val csv, graphml, croissant.json	68	1367	14148	19360	344	actor=21 athletic=4 football=3 journalist=4 painter=1 player=5 politician=13 singer=11 sport=1 writer=5	29.081
WikiProFem-test csv, graphml, croissant.json	70	1387	13642	18567	360	actor=22 athletic=3 football=4 journalist=3 painter=2 player=5 politician=11 singer=10 sport=3 writer=7	27.466
WikiProFem-m csv, graphml, croissant.json	468	8338	122728	196838	631	actor=141 athletic=25 football=24 journalist=16 painter=16 player=32 politician=81 singer=69 sport=18 writer=46	301.718
WikiProFem-m-train csv, graphml, croissant.json	330	5587	89922	140505	600	actor=98 athletic=18 football=17 journalist=9 painter=13 player=22 politician=57 singer=48 sport=14 writer=34	217.699
WikiProFem-m-val csv, graphml, croissant.json	68	1367	21978	31230	409	actor=21 athletic=4 football=3 journalist=4 painter=1 player=5 politician=13 singer=11 sport=1 writer=5	46.793
WikiProFem-m-test csv, graphml, croissant.json	70	1387	21305	29919	394	actor=22 athletic=3 football=4 journalist=3 painter=2 player=5 politician=11 singer=10 sport=3 writer=7	46.317
WikiProFem-l csv, graphml, croissant.json	468	8338	248012	413895	722	actor=141 athletic=25 football=24 journalist=16 painter=16 player=32 politician=81 singer=69 sport=18 writer=46	768.99
WikiProFem-l-train csv, graphml, croissant.json	330	5587	183710	297686	676	actor=98 athletic=18 football=17 journalist=9 painter=13 player=22 politician=57 singer=48 sport=14 writer=34	544.893
WikiProFem-l-val csv, graphml, croissant.json	68	1367	46018	67193	492	actor=21 athletic=4 football=3 journalist=4 painter=1 player=5 politician=13 singer=11 sport=1 writer=5	116.758
WikiProFem-l-test csv, graphml, croissant.json	70	1387	44193	63563	472	actor=22 athletic=3 football=4 journalist=3 painter=2 player=5 politician=11 singer=10 sport=3 writer=7	118.524

Dataset Parameters

Parameter	Value
Min valid summary edges	5
Random walk depth length	3
Min random walk number-small	100
Min random walk number-medium	150
Min random walk number-large	300
Max random walk number-small	300
Max random walk number-medium	600
Max random walk number-large	1800
Bridges number	5

Graph Structure

In the following you can see a sample of the graph format (we highly recommend using our toolkit to load the datasets):

CSV Format

After unzipping {variant}-{size}-{dataset_type}.zip file, you will find the following CSV files:

{variant}-{size}-{dataset_type}-entities.csv contains entities. An entity is a Wikidata item (node) in our
dataset.

Field	Description	datatype
id	incremental integer starting by zero	int
entity	Wikidata qid, e.g. Q76	string
wikidata_label	Wikidata label (nullable)	string
wikidata_desc	Wikidata description (nullable)	string
wikipedia_title	Wikipedia title (nullable)	string
wikipedia_id	Wikipedia page id (nullable)	long

{variant}-{size}-{dataset_type}-root-entities.csv contains root entities. A root entity is a seed node
described previously.

Field	Description	datatype
entity	id key in {variant}-{size}-{dataset_type}-entities.csv	int
category	category	string

{variant}-{size}-{dataset_type}-predicates.csv contains predicates. A predicate is a Wikidata property or a
describing
a connection.

Field	Description	datatype
id	incremental integer starting by zero	int
predicate	Wikidata Property id, e.g. P121	string
predicate_label	Wikidata Property label (nullable)	string
predicate_desc	Wikidata Property description (nullable)	string

{variant}-{size}-{dataset_type}-triples.csv contains triples. A triple is an edge between two entities with a
predicate.

Field	Description	datatype
subject	id key in {variant}-{size}-{dataset_type}-entities.csv	int
predicate	id key in {variant}-{size}-{dataset_type}-predicates.csv	int
object	id key in {variant}-{size}-{dataset_type}-entities.csv	int

{viariant}_{size}_{dataset_type}-ground-truths.csv contains ground truth triples. A ground truth triple is an
edge that
is marked as a summary for a root entity.

Field	Description	datatype
root_entity	entity in {variant}-{size}-{dataset_type}-root-entities.csv	int
subject	id key in {variant}-{size}-{dataset_type}-entities.csv	int
predicate	id key in {variant}-{size}-{dataset_type}-predicates.csv	int
object	id key in {variant}-{size}-{dataset_type}-entities.csv	int

Note: for this file one of the columns subject or object is equal to the root_entity.

Example of CSV Files

# entities.csv
id,entity,wikidata_label,wikidata_desc,wikipedia_title,wikipedia_id
0,Q43416,Keanu Reeves,Canadian actor (born 1964),Keanu_Reeves,16603
1,Q3820,Beirut,capital and largest city of Lebanon,Beirut,37428
2,Q639669,musician,person who composes, conducts or performs music,Musician,38284
3,Q219150,Constantine,2005 film directed by Francis Lawrence,Constantine_(film),1210303

# root-entities.csv
entity,category
0,Q43416,actor

# predicates.csv
id,predicate,predicate_label,predicate_desc
0,P19,place of birth,location where the subject was born
1,P106,occupation,occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2,P161,cast member,actor in the subject production [use "character role" (P453) and/or "name of the character role" (P4633) as qualifiers] [use "voice actor" (P725) for voice-only role]

# triples.csv
subject,predicate,object
0,0,1
0,1,2
3,2,0

# ground-truth.csv
root_entity,subject,predicate,object
0,0,0,1
3,3,2,0

GraphML Example

The same graph can be represented in GraphML format.

<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
    <key id="d9" for="edge" attr.name="summary_for" attr.type="string"/>
    <key id="d8" for="edge" attr.name="predicate_desc" attr.type="string"/>
    <key id="d7" for="edge" attr.name="predicate_label" attr.type="string"/>
    <key id="d6" for="edge" attr.name="predicate" attr.type="string"/>
    <key id="d5" for="node" attr.name="category" attr.type="string"/>
    <key id="d4" for="node" attr.name="is_root" attr.type="boolean"/>
    <key id="d3" for="node" attr.name="wikidata_desc" attr.type="string"/>
    <key id="d2" for="node" attr.name="wikipedia_title" attr.type="string"/>
    <key id="d1" for="node" attr.name="wikipedia_id" attr.type="long"/>
    <key id="d0" for="node" attr.name="wikidata_label" attr.type="string"/>
    <graph edgedefault="directed">
        <node id="Q43416">
            <data key="d0">Keanu Reeves</data>
            <data key="d1">16603</data>
            <data key="d2">Keanu_Reeves</data>
            <data key="d3">Canadian actor (born 1964)</data>
            <data key="d4">True</data>
            <data key="d5">actor</data>
        </node>
        <node id="Q3820">
            <data key="d0">Beirut</data>
            <data key="d1">37428</data>
            <data key="d2">Beirut</data>
            <data key="d3">capital and largest city of Lebanon</data>
        </node>
        <node id="Q639669">
            <data key="d0">musician</data>
            <data key="d1">38284</data>
            <data key="d2">Musician</data>
            <data key="d3">person who composes, conducts or performs music</data>
        </node>
        <node id="Q219150">
            <data key="d0">Constantine</data>
            <data key="d1">1210303</data>
            <data key="d2">Constantine_(film)</data>
            <data key="d3">2005 film directed by Francis Lawrence</data>
        </node>
        <edge source="Q43416" target="Q3820" id="P19">
            <data key="d6">P19</data>
            <data key="d7">place of birth</data>
            <data key="d8">location where the subject was born</data>
            <data key="d9">Q43416</data>
        </edge>
        <edge source="Q43416" target="Q639669" id="P106">
            <data key="d6">P106</data>
            <data key="d7">occupation</data>
            <data key="d8">occupation of a person; see also "field of work" (Property:P101), "position held"
                (Property:P39)
            </data>
        </edge>
        <edge source="Q219150" target="Q43416" id="P106">
            <data key="d6">P161</data>
            <data key="d7">cast member</data>
            <data key="d8">actor in the subject production [use "character role" (P453) and/or "name of the character
                role" (P4633) as qualifiers] [use "voice actor" (P725) for voice-only role]
            </data>
            <data key="d9">Q43416</data>
        </edge>
    </graph>
</graphml>