Skip to content

Latest commit

 

History

History
380 lines (337 loc) · 13.2 KB

wikiflow.md

File metadata and controls

380 lines (337 loc) · 13.2 KB
Raw

SLING Wikipedia and Wikidata processing

SLING has a task processing pipeline for downloading and processing Wikipedia and Wikidata dumps. All Wikipedia pages and the Wikidata knowledge base are freely available as dump files from Wikimedia. These dumps are processed using the SLING workflow task system to convert the dumps into SLING frame format. You can browse a pre-built knowledge base on ringgaard.com.

If you only need the final knowledge base and alias tables, you can download pre-built versions that are updated every night from Ringgaard Research:

sling fetch --dataset kb,nametab,phrasetab

Processing overview

SLING Wikipedia and Wikidata processing flow.

The Wiki processing pipeline performs the following tasks:

  • Download Wikidata and Wikpedia dumps
  • Import Wikidata dump (wikidata-import)
  • Import Wikipedia dump(s) (wikipedia-import)
  • Construct mapping from Wikipedia to Wikidata (wikipedia-mapping)
  • Wikipedia parsing (wikipedia-parsing)
  • Extract link graph from Wikipedia and Wikidata (wiki-link)
  • Merging of Wikipedia categories across languages (category-merging)
  • Inversion of category membership graph (category-inversion)
  • Compute item fan-in (item-fanin)
  • Fusing information about items to produce final item frame (item-fusing)
  • Build frame store with knowledge base (knowledge-base)
  • Extract and select aliases for entities from Wikidata and Wikipedia (name-extraction)
  • Build name table for searching for entities (name-table)
  • Build phrase table for matching phrases in text to entities (phrase-table)

After installing and building SLING, the sling command can be used for running the pipeline:

sling --help

Download dumps

First, the Wikipedia and Wikidata dumps need to be downloaded:

sling download_wikidata download_wikipedia

These dumps are large, so it might take a while to download. For example, Wikidata and just the English Wikipedia dumps together take up ~70GB space, so make sure that you have enough disk space. Additionally, you can control the download with the following flags:

  • --wikipedia YYYYMMDD Specifies the version of the Wikipedia dump. If this is not specified, the latest version available is used.
  • --wikidata YYYYMMDD Specifies the version of the Wikidata dump. If this is not specified, the latest version available is used.
  • --overwrite Allows existing local files to be overwritten when downloading new dump files.
  • --language LANG Specifies the language for Wikipedia. The default is en (English).
  • --languages LANG,... Specifies a list of language for Wikipedia. If ALL is specified, the 12 "sanctioned" languages are downloaded (en,da,sv,no,de,fr,es,it,nl,pt,pl,fi).

This will put the Wikipedia dump into data/c/wikipedia and the Wikidata dump into data/c/wikipedia.

If you have installed SLING using pip without cloning the SLING repository on GitHub, you need to download some additional files from the SLING repository:

mkdir sling
cd sling
sling fetch --dataset schemas,wikidefs,templates

After the dumps have been downloaded, the remaining processing pipeline can be executed in one go:

sling build_wiki

This is equivalent to running each of the steps separately:

sling import_wikidata
      import_wikipedia
      map_wikipedia
      parse_wikipedia
      extract_wikilinks
      merge_categories
      invert_categories
      compute_fanin
      fuse_items
      build_kb
      extract_aliases
      build_nametab
      build_phrasetab

The --language LANG flag can be used for selecting the language for Wikipedia, and the --languages LANG,... flag can be used for processing multiple Wikipedias in parallel.

If you have the lbzip2 utility installed, you can speed up the import of Wikidata by using the --lbzip2 flag. This will use lbzip2 to do decompression of the Wikidata dump in parallel.

The build_wiki pipeline needs a lot of temporary disk space to store intermediate outputs. By default it uses the TMPDIR environment variable, defaulting to /tmp. So please ensure that this folder is on a partition with enough space.

export TMPDIR=<folder on partition with lots of space>
sling build_wiki

Wikidata import

The Wikidata dump contains entities for all the items in the knowledge base in WikiData JSON format. The wikidata-import task reads these and convert them into SLING frame format and stores these in a record file set. This also outputs the schema for the Wikidata properties in SLING frame schema format. After this, the wikipedia-mapping task produces a frame store that maps from Wikipedia article ids to Wikidata QIDs.

This is an example of the SLING frame for Wikidata item Q2534120:

Q2534120: {
  =Q2534120
  :/w/item
  name: "Annette Vadim"@/lang/en
  description: "Danish actress"@/lang/en
  P26: {
    +Q383420
    P580: 1958
    P582: 1960
  }
  P21: Q6581072
  P40: Q5120414
  P214: "86528453"
  P569: 19361207
  P570: 20051212
  P31: Q5
  P19: Q26503
  P20: Q1748
  P345: "nm0883006"
  P646: "/m/02glbs"
  P27: Q35
  P268: "11957641t"
  P106: Q33999
  P106: Q4610556
  P735: Q18071263
  P213: "0000 0001 1476 8406"
  P269: "078776252"
  P1412: Q150
  P2163: "1556884"
  P2626: "226354"
  P227: "131987054"
  P2168: "247680"
  P2435: "496940"
  P2605: "79635"
  P2639: "4e701a210b1644db8c1758f49a8735b8"
  P1266: "8707"
  P2019: "p120187"
  P2604: "431759"
  P2387: "935189"
  P1196: Q3739104
  P244: "no00052596"
  P3430: "w64756mx"
  P3786: "11568"
  P2949: "Strøyberg-5"
  /w/item/wikipedia: {
    /lang/pl: "Annette Strøyberg"
    /lang/sv: "Annette Strøyberg"
    /lang/da: "Annette Strøyberg"
    /lang/de: "Annette Stroyberg"
    /lang/fr: "Annette Stroyberg"
    /lang/en: "Annette Stroyberg"
    /lang/it: "Annette Strøyberg"
  }
}

The item frame contains the id, name and optionally description of the item. An alias is generated for each label and alias for the item. The /w/item/wikipedia contains the ids for each of the Wikipedia pages for the item in different languages. One frame slot is added for each Wikidata statement for the item, e.g.

  P27: Q35

means country of citizenship is Denmark. Qualified statements are output using '+' notation, e.g.

  P26: {
    +Q383420
    P580: 1958
    P582: 1960
  }

means spouse is Roger Vadim with start time 1958 and end time 1960.

Schema frames for Wikidata properties are encoded in a similar format:

P27: {
  =P27
  :/w/property
  name: "country of citizenship"
  description: "the object is a country that recognizes the subject as its citizen"
  source: /w/entity
  target: /w/item
  P31: Q18608871
  P1647: P17
  ...
}

Wikipedia import and parsing

In contrast to Wikidata, the Wikipedia dumps are language-dependent, and there is one dump per language. By default, the English Wikipedia is used, but multiple Wikipedias in different languages can be processed by the SLING wiki processing pipeline by using the --languages flag.

The wikipedia-import task reads the Wikipedia dump and converts it into Wikipedia articles, redirects, and categories. The Wikipedia dumps are stored in XML format with the text of each page encoded in Wiki Markup Language. The wikipedia-parsing task takes these plus the Wikidata mapping and parses the documents into SLING document format. All the links in the Wikipedia articles are converted to Wikidata QIDs, and redirects are resolved to the target entity. The Wikipedia parser also outputs aliases from anchor text in the articles.

Parsed Wikipedia document for Wikidata item Q2534120:

Q2534120: {
  =/wp/en/Annette_Stroyberg
  :/wp/page
  /wp/page/pageid: 488963
  /wp/page/title: "Annette Stroyberg"
  lang: /lang/en
  /wp/page/text: "{{Use dmy dates|date=January 2014}}\n{{Infobox person\n|..."
  /wp/page/item: Q2534120
  :document
  url: "http://en.wikipedia.org/wiki/Annette_Stroyberg"
  title: "Annette Stroyberg"
  text: "<b>Annette Strøyberg</b> (7 December 1936  – 12 December 2005) was a Danish actress..."
  tokens: [{=#1
    start: 3
    size: 7
  }, {=#2
    start: 11
    size: 10
  }, {=#3
    start: 26
  }
  ...
  ]
  mention: {=#401
    :/wp/link
    begin: 13
    name: "Danish"
    evokes: Q35
  }
  mention: {=#402
    :/wp/link
    begin: 14
    name: "actress"
    evokes: Q33999
  }
  mention: {=#403
    :/wp/link
    begin: 19
    length: 3
    name: "Les Liaisons Dangereuses"
    evokes: Q1498136
  }
  mention: {=#404
    :/wp/link
    begin: 34
    length: 2
    name: "Roger Vadim"
    evokes: Q383420
  }
  ...
  /wp/page/category: Q6135380
  /wp/page/category: Q6547526
  /wp/page/category: Q7482274
  /wp/page/category: Q8362270
}

Item fusing and knowledge base

Once the Wikipedia documents have been parsed for all the languages you need, the information from these documents are collected into a Wikipedia item for each entity.

All the links in the Wikipedia documents are collected and turned into a link graph that is stored in the /w/item/links property for each item. The link graph is built over all the Wikipedias being processed. The fan-in, i.e. the number of links to the item, is also computed and stored in the /w/item/popularity property. The popularity count also includes the number of times the item is a fact target in other items.

Wikipedia categories are collected from Wikipedia documents in the category-merging task and the category membership graph is inverted in the category-inversion task, adding all the members of each category to the item for these categories.

The alias counts across all languages are used for computing an item popularity score for each item.

The Wikipedia items are consolidated with the Wikidata items in the item-fusing task into the final items. These are then used in the knowledge-basetask for building a knowledge base repository, which can be loaded into memory.

Name and phrase tables

The aliases extracted from the parsed Wikipedia documents and Wikidata are consolidated to a set of aliases for each entity in the knowledge base in the name-extraction task. This alias table is used for producing a name table repository (name-table task) which contains all the (normalized) alias phrases in alphabetical order. This is useful for incremental entity name search used by the knowledge base browser.

The phrase-table task creates a phrase table repository which can be used for fast retrieval of all entities having a (normalized) alias matching a phrase.

Browsing the knowledge base

After the wiki processing pipeline has been run, you can use the knowledge base browser for viewing the information in the knowledge base:

bazel build -c opt sling/nlp/kb:knowledge-server
bazel-bin/sling/nlp/kb/knowledge-server

If you point your browser at http://localhost:8080/kb, you can search for entities by name or id:

SLING knowledge base browser.

Datasets

The Wiki processing pipeline produces the following datasets in:

  • data/e/wiki/wikidata-items-?????-of-?????.rec (produced by wikidata-import task)
  • data/e/wiki/properties.rec (produced by wikidata-import task)
  • data/e/wiki/wikipedia-items.rec (produced by category-merging task)
  • data/e/wiki/wikipedia-members.rec (produced by category-inversion task)
  • data/e/wiki/links-?????-of-?????.rec (produced by link-graph task)
  • data/e/wiki/popularity.rec (produced by link-graph task)
  • data/e/wiki/fanin.rec (produced by item-fanin task)
  • data/e/kb/items-?????-of-?????.rec (produced by item-fusing task)
  • data/e/kb/kb.sling (produced by knowledge-base task)

For each language, the following datasets are produced:

  • data/e/wiki/<lang>/articles-?????-of-?????.rec (produced by wikipedia-import task)
  • data/e/wiki/<lang>/redirects.sling (produced by wikipedia-import task)
  • data/e/wiki/<lang>/categories-?????-of-?????.rec (produced by wikipedia-import task)
  • data/e/wiki/<lang>/mapping.sling (produced by wikipedia-mapping task)
  • data/e/wiki/<lang>/documents-?????-of-?????.rec (produced by wikipedia-parsing task)
  • data/e/wiki/<lang>/category-documents-?????-of-?????.rec (produced by wikipedia-parsing task)
  • data/e/wiki/<lang>/aliases-?????-of-?????.rec (produced by wikipedia-parsing task)
  • data/e/kb/<lang>/aliases-?????-of-?????.rec (produced by alias-extraction task)
  • data/e/kb/<lang>/name-table.repo (produced by name-table task)
  • data/e/kb/<lang>/phrase-table.repo (produced by phrase-table task)