I tried to order the list alphabetically by last name...but in some cases I was not sure
| Name | Affiliation | Twitter (optional) | |
|---|---|---|---|
| Ammar Ammar | [email protected] / [email protected] | Maastricht University | @ammarECR |
| Guillermo Benjaminsen | [email protected] / [email protected] | Google (intern), Universidad de Buenos Aires | @guillebenj |
| Dan Brickley | [email protected] | Google, London UK. | @danbri |
| Alejandro González Hevia | [email protected] | University of Oviedo, Spain | |
| Jose Emilio Labra Gayo | [email protected] | University of Oviedo, Spain | @jelabra |
| Eric Prud'hommaux | [email protected] | Janeiro Digital, W3C/MIT | what's a Twitter? |
| Denise Slenter | [email protected] | Maastricht University | @SMaLLCaT4Sci |
| Harold Solbrig | [email protected] | Johns Hopkins University | |
| Seyed Amir Hosseini Beghaeiraveri | [email protected] | Heriot-Watt University, UK. | |
| Benno Fünkfstük | [email protected] | TU Dresden | |
| Andra Waagmeester | [email protected] | Micelio / Gene Wiki | @andrawaag |
| Liza? |
Contacts: Twitter: @jelabra, Github: labra
- Shape Expressions, Wikidata, Wikibase
- SPARQL
Contacts: Twitter: @andrawaag, Github: Andrawaag
Wikidata is growing by the day, leading to more and more timeouts on relatively simple queries (e.g. Give me all Wikidata items with a DOI.) With the support of ShEx in Wikidata in its EntitySchema extension it is possible to draw the bounderies between a subset of Wikidata of interest. During the biohackathon I would like to work on enabling a workflow, to based on a Shape Expression, generate this subset. Two main use-cases that comes to mind are: 1. Creating a subset to enable more complex queries by loading that subset in a local RDFStore. 2. Create backup subsets for future/persistent reference.
- Shape Expressions, Wikidata, Wikibase
- Wikidata Integrator
- Python
- SPARQL
Contacts: Github: alejgh
Continue development of Wikidata to Wikibase subsetting prototype (wbs_core in WikidataIntegrator). Can also help with adding import to PyShEx.
- Python
- PyShEx
- Wikidata Integrator
- Wikidata and SPARQL
Contacts: Github: ammar257ammar
I want to create a subset of Wikidata containing the data topics supported by Scholia
- ShEx
- RDF ETL
- Scholia
- Wikidata and SPARQL
Contacts: Github: denisesl22
Want to use knowledge learned here to implement ShEx for WIkiPathways RDF after BioHackathon.
- RDF Wikidata + WikiPathways
- SPARQL
- Python, R
Collect some examples of ShEx schemas as a running example
- Use slurp from ShEx validators to populate another Wikibase
-
Decisions taken:
- Keep "Slurper" name
-
Why ShEx?
- Leverage community-developed schemas for subject matter
- Can implement context-specific queries that would be daunting or near impossible in pure SPARQL
- Theoretically - self documenting...
-
Why NOT ShEx for execution?
- Will it fix the performance issues?
- Some (e.g. python) ShEx implementations have their own performance issues
-
Approaches
- Slurp: cache in an triple store results of every query executed during validation.
- Results: extract the triples involved in validation
- Compiled Query: walk the schema and compile to SPARQL queries
- complex queries would extract exact set which map to Slurp results
- simpler queries would extract a superset
-
Using an intermediate representation of Wikidata?
- Plain RDF vs JSON...
- Design patterns for ShEx
- "Hello World" of ShEx slurping - meaningful example of
- Human gene: https://www.wikidata.org/wiki/EntitySchema:E37
- WikidataSubsetting
- Yashe editor - http://www.weso.es/YASHE/
- Jose Labra - Create a ShEx based on the Gene Wiki paper. Done, see shex file
- Ammar Ammar - Create a ShEx for one use case from Scolia and apply it using ShEx-JS/YASHE
- EricP - Command line slurper
- Alejandro - Look to pyshex to see if it's possible to add imports
- Andra - Compare the wdt (truthy) shape expressions from Jose and create the p equivalent.
- Danbri - Figure out how to host demos on public Google cloud projects (boring but it blocked me since biohackathon 2019!)
We developed a simple demo in a Jupyter Notebook where we used PyShEx to print a subset in ttl from the biomedical ShEx file: see notebook here.
Harold: https://github.com/hsolbrig/PyShEx/blob/master/notebooks/WikiSlurper.ipynb
Guillermo: provided some sparql queries based on Andra's life science subset graph, trying to help in replicating the graph
- Jose Labra: Prepare tutorial on ShEx/Wikidata. Implement slurp generation from ShEx-s
- Alejandro: Create command line script to generate subsets with PyShEx, work in implementing import functionality in PyShEx.
- Ammar: writing more Scholia ShEx templates and run the slurper from PyShEx against Wikidata (check performance and effeciency)
- Seyed: Installing/reviewing WDumper
- Denise: Locate ShEx which are relevant for Wikidata Chemistry(/Metabolite) related entities, create list of missing ShEx.
Tasks done:
- Jose Labra: Prepared ShEx/entity schemas intro
- Alejandro:
- Harold:
- Eric:
Dan's discussion about domain specific language to describe wikidata subsettings, which could generate ShEx schemas/SPARQL queries.
Separate language for wikidata:
{ "anatomical_structure":
{ "on-type": "wd:Q4936952",
"wdt:P361": "anatomical_structure",
"wdt:P527": "anatomical_structure" },
"wikidata-specific-magic-extras": "GOODTRIPLES WITHREFS FOOBAR"
{ // etc.
}
}
Use case about automatic fact-checking using wikidata
Invited people: Kat Thornton, Nishad Thalhath, Tom Baker, Anastasiia
Discussion about WDump/Wikidata subsetting language Authorship of Entity schemas at Wikidata
Tasks for tomorrow:
- Dan, connect to the WDump tool's author
- Connect with entity schemas/wdumper
- Eric, continue with slurper
- Guillermo, look at wdumper
- Kat, look for interesting entity schemas
- Finn's entity schemas
- Denise, chemistry oriented entity schemas
- Prototype of a schema around Chemistry
- Alejandro, finish implementation of subsetting script using PyShEx.
- Seyed: Continue working with Wdump
We start the day noticing that there is a issue with Wikidata's RDF representation that returns blank nodes.
-
ShEx template used: https://raw.githubusercontent.com/kg-subsetting/biohackathon2020/main/use_cases/scholia/organization.shex
-
The query used to get the items:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?item WHERE {?work wdt:P50 / (wdt:P108 | wdt:P463 | (wdt:P1416/wdt:P361*)) wd:Q27177633. ?item wdt:P2860 ?work.} LIMIT 100- The query that contains the blank node where the exception in PyShEx is raised:
SELECT ?s ?p ?o (isBlank(?o) as ?isBlank) {<http://www.wikidata.org/entity/Q313093> <http://www.wikidata.org/prop/direct/P184> ?o}s:Q42-bf7e1294-4f0f-3511-ab5f-81f47f5c98cb a wikibase:Statement ;
pq:P3680 _:4249d9c21f8b973644e0eab84cdaaf17 ;
...wdno:P31 a owl:Class ;
owl:complementOf _:0b8bd71b926a65ca3fa72e5d9103e4d6 .
_:0b8bd71b926a65ca3fa72e5d9103e4d6 a owl:Restriction ;
owl:onProperty wdt:P31 ;
owl:someValuesFrom owl:Thing .During the biohackathon 2020 where we are working on subsetting wikidata, we ran into the issue of blank notes being used in the RDF of Wikidata to express unknown and no values. Unfortunately this isn't consistent because blank notes are also used to express other things such as owl:complementOf (e.g. Q42).
These blank nodes are also problematic for anything that traverses wikidata node-by-node such as faceted browsers or ShEx validators.
It is not explicitly incorrect to have blank nodes in RDF data, but it is:
- inconsistent with the approach that Wikidata has taken (which is to avoid blank nodes)
- ambiguous because in RDF, blank nodes do not imply unknown values, they are simply unidentified nodes in the graph.
Steps to Reproduce:
- GET http://www.wikidata.org/entity/Q313093.ttl
- look for "_:" (currently _:2d22892344b969be376b57170b5e495f)
- try a SPARQL query for all properties of that node
SELECT ?P ?o { _:2d22892344b969be376b57170b5e495f ?p ?o } - Because of the semantics of SPARQL, this will try to get every triple in the database.
Remedy:
Invent a system-wide identifier for unknown values and use that Q identifier for all references to unknow value, e.g. change:
wd:Q313093 wdt:P184 _:2d22892344b969be376b57170b5e495f
to:
wd:Q313093 wdt:P184 wd:Q98765
When
- ShEx template used: https://raw.githubusercontent.com/kg-subsetting/biohackathon2020/main/use_cases/scholia/organization.shex
The query used to get the items:
PREFIX wdt: http://www.wikidata.org/prop/direct/ PREFIX wd: http://www.wikidata.org/entity/
SELECT DISTINCT ?item WHERE {?work wdt:P50 / (wdt:P108 | wdt:P463 | (wdt:P1416/wdt:P361*)) wd:Q27177633. ?item wdt:P2860 ?work.} LIMIT 100 The query that contains the balnk node where the exception in PyShEx is raised: SELECT ?s ?p ?o (isBlank(?o) as ?isBlank) {http://www.wikidata.org/entity/Q313093
- Matched graph
- Exact triples that have been used when validating
- Slurp graph
- The neighbourhood of the items that are part of the validation
- Mapping/transformig while slurping
Ammar's raised the issue of confronting "too many requests" when validating real wikidata
- Ammar attempted to generate slurps...several problems detected meanwhile:
- Wikidata's limitations
- Blank nodes
- Too many requests
- Wikidata's limitations
- Dan exchanged info with WDump's author who is planning to join us
- Guillermo: problems installing WDumper gradle
- Labra: Slide 7 Map of approaches
- Alejandro: Creation of a command line script that generates a subset to a ttl file.
- Andra talked about KGTK: https://kgtk.readthedocs.io/en/latest/
- Eric: Transform the GeneWiki ShEx to the Json format needed by WDumper
- Guillermo: Convert the GeneWiki/Json to SPARQL queries
- 15:30h Participants: Liza Ovchinnikova, Alasdair Gray, Ivan Micetic, Dan Brickley, Eric Prud'hommeaux, Guillermo B., Andra Waagmeester, Petro Papadopoulos, Denise
- Creating subsets and converting them to other useful schemas
- ShEx patterns for markup
- Vocab mappings
Similar use cases: Underlay
Taxon --- schema from bioschemas?
- Type inspired by DarwinCore and reuses similar properties
- Separates the Taxa from the name associated with it
- Name modelled as a TaxonName
Talk with Benno Fünfstück, author of WDumper about the tool.
- User's feedback about what kind of dumps they create?
- The dump is compressed
- Talk about the JSON configuration file
- It works on a local dump of wikidata
- It is based on Wikidata Toolkit. API
- No useful for graph-level queries
- We can obtain a subset of Wikidata if we know the Properties...but not a cyclic data model where we go from severl items
:gene EXTRA wdt:P31 {
wdt:P703 @:taxon * ;
wdt:P684 @:gene * ;
wdt:P682 @:biological_process ;
wdt:P688 @:protein * ;
wdt:P527 @:biological_pathway *;
wdt:P1057 @:chromosome ;
}{ "entities": [ // OR'd
{ "type": "item", "properties": [ // AND'd
{ "type": "entityid",
"value": "Q7187", // "gene"
"property": "P31" } ] },
{ "type": "item", "properties": [ // AND'd
{ "type": "entityid",
"value": "Q7187b", // "gene subclass 1"
"property": "P31" } ] }
],
"labels": true, "aliases": true,
"sitelinks": true, "truthy": false, "meta": true, "descriptions": true,
"statements": [
{ "qualifiers": false, "full": false,
"references": false, "simple": true
},
{ "properties": [
"P703", // taxon
"P684", // ortholog_gene
"P682", // biological_process
"P688", // protein_encoded_by_gene
"P527", // has_part
"P1057" // chromosome
],
"full": true, "simple": false, "references": false,
"qualifiers": false, "rank": "non-deprecated"
}
]
}ericP: I scripted a dump for getting all the triples from the entities of interest by following this template:
{
version: 1,
__name: sh.id.substr(NS_ex.length),
entities: [
{
id: id++,
type: "item",
properties: [
{
id: id++,
type: "entityid",
rank: "all",
value: type,
property: ""
}
]
}
],
meta: true,
aliases: true,
sitelinks: true,
descriptions: true,
labels: true,
statements: [
{
id: id++,
qualifiers: false,
simple: true,
rank: "all",
full: false,
references: false
}
]
}
The only inputs there are the __name which was just for readers' orientation (would wdumper safely ignore that property?), the value on the only entity property, and three places where I saw ids in the output.
I collected all of the dump configs into an array below. (Would wdumper accept such a packaging of multiple dump configs?)
How would I upload configs (vs. using the UI) to start a job?
./cli.js -x ../../use_cases/genewiki/genewiki.shex
skipping http://example.org/biological_process: TypeError: Cannot read property 'expressions' of undefined
skipping http://example.org/chromosome: TypeError: Cannot read property 'filter' of undefined
skipping http://example.org/mechanism_of_action: TypeError: Cannot read property 'filter' of undefined
skipping http://example.org/molecular_function: TypeError: Cannot read property 'expressions' of undefined
skipping http://example.org/symptom: TypeError: Cannot read property 'filter' of undefined
skipping http://example.org/taxon: TypeError: Cannot read property 'filter' of undefined
[
{
"version": 1,
"__name": "active_site",
"entities": [
{
"id": 0,
"type": "item",
"properties": [
{
"id": 1,
"type": "entityid",
"rank": "all",
"value": "Q423026",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 2,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "anatomical_structure",
"entities": [
{
"id": 3,
"type": "item",
"properties": [
{
"id": 4,
"type": "entityid",
"rank": "all",
"value": "Q4936952",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 5,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "binding_site",
"entities": [
{
"id": 6,
"type": "item",
"properties": [
{
"id": 7,
"type": "entityid",
"rank": "all",
"value": "Q616005",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 8,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "biological_pathway",
"entities": [
{
"id": 9,
"type": "item",
"properties": [
{
"id": 10,
"type": "entityid",
"rank": "all",
"value": "Q4915012",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 11,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
[],
{
"version": 1,
"__name": "chemical_compound",
"entities": [
{
"id": 12,
"type": "item",
"properties": [
{
"id": 13,
"type": "entityid",
"rank": "all",
"value": "Q11173",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 14,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
[],
{
"version": 1,
"__name": "disease",
"entities": [
{
"id": 15,
"type": "item",
"properties": [
{
"id": 16,
"type": "entityid",
"rank": "all",
"value": "Q12136",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 17,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "gene",
"entities": [
{
"id": 18,
"type": "item",
"properties": [
{
"id": 19,
"type": "entityid",
"rank": "all",
"value": "Q7187",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 20,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
[],
{
"version": 1,
"__name": "medication",
"entities": [
{
"id": 21,
"type": "item",
"properties": [
{
"id": 22,
"type": "entityid",
"rank": "all",
"value": "Q12140",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 23,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
[],
{
"version": 1,
"__name": "pharmaceutical_product",
"entities": [
{
"id": 24,
"type": "item",
"properties": [
{
"id": 25,
"type": "entityid",
"rank": "all",
"value": "Q28885102",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 26,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "pharmacologic_action",
"entities": [
{
"id": 27,
"type": "item",
"properties": [
{
"id": 28,
"type": "entityid",
"rank": "all",
"value": "Q50377224",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 29,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "protein_domain",
"entities": [
{
"id": 30,
"type": "item",
"properties": [
{
"id": 31,
"type": "entityid",
"rank": "all",
"value": "Q898273",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 32,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "protein_family",
"entities": [
{
"id": 33,
"type": "item",
"properties": [
{
"id": 34,
"type": "entityid",
"rank": "all",
"value": "Q417841",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 35,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "protein",
"entities": [
{
"id": 36,
"type": "item",
"properties": [
{
"id": 37,
"type": "entityid",
"rank": "all",
"value": "Q8054",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 38,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "ribosomal_RNA",
"entities": [
{
"id": 39,
"type": "item",
"properties": [
{
"id": 40,
"type": "entityid",
"rank": "all",
"value": "Q28885102",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 41,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "sequence_variant",
"entities": [
{
"id": 42,
"type": "item",
"properties": [
{
"id": 43,
"type": "entityid",
"rank": "all",
"value": "Q15304597",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 44,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
{
"version": 1,
"__name": "supersecondary_structure",
"entities": [
{
"id": 45,
"type": "item",
"properties": [
{
"id": 46,
"type": "entityid",
"rank": "all",
"value": "Q7644128",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 47,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
},
[],
[],
{
"version": 1,
"__name": "therapeutic_use",
"entities": [
{
"id": 48,
"type": "item",
"properties": [
{
"id": 49,
"type": "entityid",
"rank": "all",
"value": "Q50379781",
"property": ""
}
]
}
],
"meta": true,
"aliases": true,
"sitelinks": true,
"descriptions": true,
"labels": true,
"statements": [
{
"id": 50,
"qualifiers": false,
"simple": true,
"rank": "all",
"full": false,
"references": false
}
]
}
]
This is the final day. We started looking at the slides/report
Andra said he has been creating a Wikibase instance to allocate the subset and raises the concern that uploading the RDF dump through Wikibase API can be slow. It would be more efficient to directly upload it through Blazegraph or GraphDB.
THis is the current target wikibase running on gcloud: http://35.205.156.230:8181/
and the incomplete on wbstack: https://bh20subset1.wiki.opencura.com/wiki/Main_Page
Ammar also tried ShapeDesigner (ShEx java implementation) and it hanged on the same place (same entity) that have a blank node and the query was actually having the blank node as subject and it was trying to fetch everything from Wikidata.
So basically until this moment: all available implementations of ShEx slurpers (JavaScript "shex.js" /Python "PyShEx" / Java "ShapeDesigner") do not have a workaround for this, so maybe it should be dealt with in the future to make it feasible for Wikidata ShEx slurping.
-
Meeting to finish the Chemistry Entity schema, Denise, Seyed joining ShEx CG
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Join next virtual SWAT4HCLS hackathon to continue working on this
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Continue working on handling slurper with blank nodes and solve issue with ShEx working on SPARQL endpoints
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Eric: Experimental "slurper" which, instead of querying the SPARQL endpoint, gets data from the .ttl files for the queried entity.
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WDumper??
- Add feature about graph traversing?
- Review and run the JSON config files that were generated (Seyed/Eric)
- Local installation of WDumper (Seyed)
- requires an entire dump of Wididata JSON (~17G zipped)
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Wikidata Subsetting Language?? (JSON)
- Seyed
-
ShEx hackathon/hands-on event every 2 weeks (alternating with CG meeting)
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
prefix : <http://example.org/>
import ....
:chemicalsOrSubClassOf {
wdt:P31
}
# wdt:P279 = rdfs:subClassOf
# wdt:P31 = rdf:type
# wdt:P527 = has part
# wd:Q11173 = Chemical Compound
/* ShEx language ideas:
Discriminator { wdt:P31/wdt:P279* [wd:Q11173] }
...
IF { wdt:P31/wdt:P279* [wd:Q11173]} THEN {
...
}
NOT { } OR { ....}
*/
:chemical {
# discriminator
# wdt:P31/wdt:P279* [ wd:Q11173 ]
^wdt:P527 @:biological_process * ; # only get checmicals part of a biological_prrocess
^wdt:P527 . * ; # get all
wdt:P3771 . * ; # activator_of
wdt:P129 . * ; # physically interacts with
wdt:P2868 . * ; # subject has role
wdt:P361 . * ; # part of
wdt:P703 . * ; # found in taxon
wdt:P231 . ? ; # CAS registry number
wdt:P661 . ? ; # ChemSpider ID
# ...
wdt:P6889 . * ; # MassBank accession number
# ...
# p:P31 { ps:P31 [ wd:Q11173 ] }
}
:biological_process EXTRA wdt:P527 {
wdt:P527 @:chemical OR . * ;
^wdt:P527 @:biological_pathway *
}
:biological_pathway {
wdt:P527 @:biological_process
}
:medication {
}
[](https://hackmd.io/5nKOyk8qQTO5DSCa_M5p3g)