Interpreting Open-Domain Modifiers: Decomposition of W ikipedia Categories into Disambiguated Property-Value Pairs (2020)

Abstract: This paper proposes an open-domain method for automatically annotating modifier constituents (20th-century’) within Wikipedia categories (20th-century male writers) with properties (date of birth). The annotations offer a semantically-anchored understanding of the role of the constituents in defining the underlying meaning of the categories. In experiments over an evaluation set of Wikipedia categories, the proposed method annotates constituent modifiers as semantically-anchored properties, rather than as mere strings in a previous method. It does so at a better trade-off between precision and recall.

## introduction motivation: as web search moves towards returning structured answers rather than flat sets of document links in response to users' queries, the need for high-quality, wide-coverage knowledge to support such answers is growing stronger. the largest of the existing knowledge repositories @xcite @xcite , whether publicly available @xcite or restricted to commercial access @xcite , uniformly rely on data in wikipedia for their core sets of topics and knowledge assertions. in addition to its role in web search and information retrieval @xcite @xcite , wikipedia and the knowledge repositories derived from it are useful in a growing variety of tasks. such tasks pertain to text analysis @xcite and, specifically, knowledge acquisition from text @xcite @xcite . millions of wikipedia articles are connected to parent categories, which are in turn connected to their own, iteratively broader categories. for example, the article "art:gary oldman" is connected to parent categories such as "ctg:20th-century english male actors", "ctg:alumni of rose bruford college", which are in turn connected to their own, broader categories such as "ctg:actors", "ctg:acting", "ctg:language". some categories really correspond to individual topics, e.g., "ctg:rose bruford college". many other categories in wikipedia -hundreds of thousands, by our estimates -each corresponds to a fine-grained class that groups together individual articles sharing common properties. for example, the category "ctg:20thcentury english male actors" groups articles such as "art:gary oldman" and "art:jude law", which conceptually share properties that could be described as "born or living in the 20th-century", "born in england", "being a male" and "being actors". that wikipedia organizes topics into hundreds of thousands of potential fine-grained classes is remarkable. comparatively, topics in other knowledge repositories are organized into only hundreds of types, in dbpedia @xcite ; or thousands of collections, in freebase @xcite . existing applications @xcite that take advantage of wikipedia categories include the creation of large, deep, fine-grained hierarchies out of wikipedia articles and their categories @xcite . unfortunately, in both wikipedia and downstream applications, wikipedia categories are represented as nothing more than mere strings. their meaning is otherwise not captured. understanding and annotating the meaning of wikipedia categories would make them more useful and increase their impact. contributions: the main contributions of this paper are as follows. first, it provides a precise, semantically-anchored understanding of the role of the constituents in defining the underlying meaning of wikipedia categories. for this purpose, it pro-poses an open-domain method for annotating modifier constituents within categories with properties and values referred to by modifier constituents. previous work @xcite annotates categories with isolated, ambiguous strings such as "century" for the constituent "20th-century" within the category "ctg:20th-century english male actors". in contrast, the method proposed here annotates categories with non-ambiguous values that are wikipedia articles or wikidata topics, such as "val:20th century" for the same constituent "20th-century" within "ctg:20th-century english male actors". more importantly, it also annotates categories with properties with well-defined descriptions and semantic meaning in wikidata @xcite , thus annotating the same constituent "20thcentury" with the property "prp:p569 (date of birth)" from wikidata. second, the paper is the first to investigate the role of wikidata in automatically enriching wikipedia categories. in contrast, previous methods for open-domain information extraction mostly rely on unstructured or semi-structured text @xcite , wikipedia @xcite and repositories other than wikidata @xcite @xcite with few exceptions @xcite . third, in experiments over the gold set of wikipedia categories, in comparison to a previous method @xcite , the proposed method automatically annotates constituent modifiers as semantically-anchored properties and topics, rather than mere strings. it does so at a better trade-off between precision and recall. ## annotating categories notations: the following prefixes distinguish among the various kinds of items: art as in "art:gary oldman", for a wikipedia article ( http://en.wikipedia.org/wiki/gary oldman); ctg as in "ctg:20th-century english male actors", for a wikipedia category ( http://en.wikipedia.org/wiki/ category:20th-century english male actors); tpc as in "tpc:gary oldman", for a wikidata topic ( http://www.wikidata.org/wiki/q83492 ), which often has an equivalent wikipedia article ("art:gary oldman"); prp as in "prp:p569 (date of birth)", for a wikidata property ( http://www.wikidata.org/ wiki/property:p569); val as in "val:20th century", for the value of a property of a topic in wikidata. goal: finer-grained categories in wikipedia often take the form of compositional noun phrases. within such categories, individual modifier constituents refer to values that implicitly allude to explicit properties applying to, and shared by, the descendant wikipedia articles located under the categories. for example, the modifier constituent "english" alludes to an explicit property regarding the place of birth applying to "art:gary oldman", "art:jude law" and other descendant wikipedia articles located under the category "ctg:20th-century english male actors". categories are represented simply as strings in wikipedia. understanding the role played by as many of their individual constituents as possible, by accurately identifying the explicit properties to which their constituents implicitly refer, would go a long way in understanding the overall meaning of the categories. it is the main goal of this paper. ## experimental setting data sources: the experiments operate over english snapshots of wikipedia and wikidata from june 2018. as in previous work @xcite , wikipedia articles are automatically discarded if they are disambiguation or redirect pages. similarly to @xcite , wikipedia categories are automatically discarded if they are meant for wikipedia's internal bookkeeping, as approximated by the presence of the subphrases article(s), category(ies), infobox(es), pages, redirects, stubs, tem-plates, wikiproject, use mdy dates, lists, stubs or wikidata in their names. finally, as in @xcite @xcite , categories are automatically discarded if they likely correspond not to classes but rather to individual topics. in this case, such categories are approximated by the absence of any plural-form tokens (based on lemmatization data in wordnet), thus discarding, e.g., "ctg:rose bruford college". alternatively, previous work on distinguishing wikipedia articles that are classes @xcite could be extended to wikipedia categories. the filtered wikipedia snapshot connects 5,101,643 articles to 1,124,679 categories. by traversing chains of wikidata property-value pairs whose property is "prp:p131 (located in the administrative territorial entity)", some of the existing location-based data in wikidata is automatically expanded. for example, given the existing property-value pair "prp:p19 (place of birth)" and "tpc:london" for some wikidata topic, additional property-value pairs like "prp:p19 (place of birth)" and "tpc:greater london", or "prp:p19 (place of birth)" and "tpc:london", are added to the same wikidata topic. some of the temporal values in wikidata are also automatically expanded. for any property-value pairs whose values are encoded as dates in wikidata, additional propertyvalue pairs are generated by a) selecting only the years; and also b) replacing the years with corresponding decades and centuries. for example, additional values generated starting from the value "21 march 1958" include "tpc:1958", "tpc:1950s" and "tpc:20th century". extraction parameters: property annotations extracted by the proposed method are discarded if they are one of the two properties used in wikidata for organizing topics hierarchically, namely "prp:p31 (instance of)" or "prp:p279 (subclass of)". during the alignment of modifier constituents from categories to values of properties from wikidata, the two strings being compared are considered to match if, after conversion to lowercase, their lemmas @xcite or stems are either identical or one is an adjectival form and the other is the corresponding nominal form in wordnet, e.g., "english" vs. "england". ## related work as it extracts semantic annotations over opendomain concepts (namely, over categories from wikipedia), the proposed method falls under the area of open-domain information extraction @xcite @xcite @xcite @xcite . previous work in that area often uses wikipedia data @xcite @xcite . in previous work, annotations for modifier constituents within compositional noun phrases may be extracted out of an unbound set of ambiguous strings, with no explicit semantics and possibly redundant ("from", "born in", "born at") @xcite . alternatively, when annotations are selected out of a small, manually-created set of candidate annota-tions @xcite , they are too coarse-grained to be equivalent to born in or headquartered in etc. the method introduced in @xcite decomposes compositional wikipedia articles into constituent wikipedia articles. for example, it decomposes "art:swiss passport" into "art:switzerland", "art:passport". it does not attempt to otherwise understand or annotate the semantics of the constituents. it is applicable only to wikipedia articles, although many more wikipedia categories are compositional. the method in @xcite extracts annotations over child categories based on their parent categories in wikipedia. the method produces superior annotations to previous efforts @xcite to annotate categories based on data within wikipedia itself. it extracts annotations that are strings without any associated descriptions or disambiguation. in contrast, the method proposed here extracts annotations as properties ("prp:p569 (date of birth)") with defined descriptions and semantic meaning in wikidata. it also disambiguates modifier constituents to the corresponding wikidata topics or, if available, to corresponding wikipedia articles. such annotations and disambiguation add a layer of semantic understanding to hierarchies of articles and categories extracted from wikipedia @xcite , wherein categories are otherwise represented only as strings. ## conclusions this paper takes advantage of data from wikidata, to extract annotations for understanding the role played by various constituents in determining the meaning of wikipedia categories. unlike in previous work, the annotations are semanticallyanchored properties and values, rather than ambiguous strings. they offer a better trade-off between precision vs. recall. current work explores the utility of alternative sources besides wikidata, in increasing the coverage of the annotations; and the role of the annotations in generating plausible categories for wikipedia articles.