Provenance for Linguistic Corpora through Nanopublications (2020)

Abstract: Research in Computational Linguistics is dependent on text corpora for training and testing new tools and methodologies. While there exists a plethora of annotated linguistic information, these corpora are often not interoperable without significant manual work. Moreover, these annota-tions might have evolved into different versions, making it challenging for researchers to know the data’s provenance. This paper addresses this issue with a case study on event annotated corpora and by creating a new, more interoperable representation of this data in the form of nanopublications. We demonstrate how linguistic annotations from separate corpora can be reliably linked from the start, and thereby be accessed and queried as if they were a single dataset. We describe how such nanopublications can be created and demonstrate how SPARQL queries can be performed to extract interesting content from the new representations. The queries show that information of multiple corpora can be retrieved more easily and effectively because the information of different corpora is represented in a uniform data format.

## introduction the availability of annotated linguistic corpora is crucial to develop natural language processing (nlp) systems @xcite . in the past couple of decades, many linguistic resources have been released, which contain different types of annotations, from morphosyntactic to semantic and discourse level annotations. however, they often lack structural and conceptual interoperability @xcite . the former is related to the data format of annotations, such as xml-standoff or rdf representations, while the latter refers to the possibility of exchanging information in a consistent and mappable way. diverging annotation guidelines, the structure of annotated output, and the different amounts of annotations created per corpus pose a challenge in organizing the provenance of corpora. often, annotation projects run on (subsets of) existing text corpora, which are thereby annotated with multiple annotation layers. unfortunately, the format for linking annotations to the texts is mostly not standardized and these links therefore are often not fully precise or directly interoperable. this makes it challenging for a researcher to figure out the data's exact provenance and to integrate annotations from several corpora. integrating different annotations is valuable because it can help scholars study and understand the different interdependencies between annotation layers (e.g. semantic parsers usually take syntactic structure in consideration). moreover, often the annotations follow idiosyncratic guidelines that pursue a specific annotation goal. the need to organize the various existing annotations has been recognized by the corpus linguistic community @xcite . while a number of solutions to improve linguistic linked data have been presented in the past, we propose here a novel approach that uses the linked data format of nanopublications to represent annotated corpora in a more fine-grained semantic format, with the aim of boosting the interoperability of linguistic corpora and facilitating the automatic integration of annotations in a reliable and transparent manner. our research is motivated by the empirical analysis on 20 event-annotated corpora presented in @xcite , which highlighted the challenges, as well as the opportunity, of event corpora interoperability. existing event annotation standards range from annotations about the participants, timing/temporal order, factuality, and entity coreference relation, making a standardized description of an event difficult. this is where nanopublications as a fine-grained and provenance-aware data format could provide transparency and interoperability for computational linguistic research. for our case study, we have chosen to focus on integrating annotations from two corpora, factbank @xcite and parc 3.0 @xcite . in parc, attribution relations and their components (cue, content, source) are annotated, while in factbank events and their factuality values (i.e. the certainty of the occurrence of an event) are annotated. it is interesting to combine the two annotation layers in order to extract, for example, which events occur in the content of attribution relations and what are their factuality values. figure 1 presents the same sentence annotated in parc and factbank. our main contributions thereby are (1) providing a fine-grained and interoperable linked data representation of annotated linguistic corpora in the form of nanopublications, (2) analysing the main interoperability problems that we encountered and solved with our nanopublication-based approach, and (3) demonstrating how the concrete annotations from our case study of two corpora can be integrated with nanopublications and queried with sparql. we describe below how we converted these corpora into nanopublications and then report on the interoperability challenges faced and solved with our approach by representing the data in a uniform manner using nanopublications. finally, we discuss based on our results the extent to which nanopublications can be seen as a viable alternative for improved linguistic corpora interoperability. ## linked data, data provenance and nanopublications linked data is about connecting and publishing data in a structured way on the web, often on the basis of an ontology using the web ontology language (owl) @xcite . the data is often structured in triples using the resource description framework (rdf). by using unique uris for each entity of information, these entities can be interlinked in order to create an entire web of data @xcite . several projects were already performed to create linked linguistic data. since 2012, six series of linked data in linguistics (ldl) workshops have been hosted to gather and discuss contributions promoting linking linguistic data. after the second workshop, one of the presented efforts was the linked linguistic open data (llod) cloud. 1 while creating the llod cloud, a lot of linguistic data was already available, which were mostly represented using rdf. one example is wordnet, which is also part of the semantic web @xcite . furthermore, chiarcos proposed to represent linguistic corpora into owl and rdf to interlink all of the different resources of corpora. in this way, the annotations of the corpora could be linked using terminological resources like standardized annotation formats @xcite . existing approaches that aim to represent the structure and content of natural language and its annotations include the ontology lexicalisation and the ontologies of linguistic annotation (olia) @xcite @xcite . olia focuses on annotations of linguistic corpora and can be seen as a source that references to the 'annotation terminology' that can be used in combination with the llod to capture all of the information of the annotations in the llod in a similar format @xcite . since all different texts and annotations in a corpus may have a different origin, i.e. provenance, provenance ontology prov foot_1 can be used for this. this ontology contains different classes and properties that represent the provenance information in different contexts, thereby usable for keeping track of the provenance information of linguistic corpora. the prov ontology has been shown to be applicable to a diversity of fields to track provenance information in a general manner @xcite . even though the rdf language is not optimized for this, the nlp interchange format (nif) foot_2 makes it possible to represent texts and their elements in rdf, primarily by using strings. with the nif ontology, a context, sentence, phrase, or word can be represented into rdf triples. it is also possible to have references between different levels, so a word can reference to another part of the rdf scheme that is the sentence from where it was derived. in a study by @xcite it was suggested to improve the reprensentation of the provenance information of the annotations in the nif ontology by introducing a new ontology called mond, which uses the prov ontology to include provenance information in the nif ontology @xcite . moreover, many annotation guidelines exist and each is usually represented in a different structure, increasing the difficulty in creating a standard model to transform annotations into rdf. the web annotation vocabulary @xcite , for example, provides a possible solution with relations such as 'motivatedby' and 'hastarget', making it possible to structure annotations in an interoperable way. nanopublications are a format for small data publications based on rdf triples, consisting of three parts: the assertion, provenance, and publication information @xcite . the assertion contains the main content of a nanopublication, for example stating in a formal way the link between a gene and a disease. the provenance part states how this assertion came to be, by linking to the study that was performed or the paper from which the assertion was extracted. the publication information part, finally, records information about the nanopublication itself, such as by who and when it was created @xcite . in a previous work, a java library for nanopublications was created, which can also be used as a command line tool @xcite . nanopublications can be given trusty uris as identifiers, which include a hash value of the complete content, and thereby make nanopublications immutable and verifiable @xcite . such nanopublications can then be reliably and redundantly published to the existing distributed server network @xcite . each of these servers contains all nanopublications, making it possible to retrieve the nanopublication from another server when one server is down. nanopublications also allow for precise and reliable versioning, as well as the definition of incremental datasets by defining nanopublication indexes @xcite . such indexes are represented as nanopublications themselves that contain links to other nanopublications and thereby defining sets of nanopublications. ## methodology in this section we introduce our methodology to address the above-mentioned problems of interoperability and provenance of text corpora by applying the concept and techniques of nanopublications. to demonstrate and evaluate this methodology, we then present a case study. we introduce a number of questions on the combined annotations that can be answered in an integrated and automatic manner through sparql queries. through the sparql queries we will show that data of multiple corpora can be retrieved using a single query, solving the interoperability issues. ## case study we applied the nanopublication-based approach to the case study in order to address the problem of interoperability and provenance. different types of nanopublications were created to represent the chosen corpora. as introduced above, nanopublications consists of an assertion, provenance, and publication info part. in these nanopublications the publication info part is similar for all our nanopublications, containing the date of creation, license, orcid identifiers of the creators, and sometimes further comments and website links. all the text and word nanopublications, as well as the annotations of factbank, are also marked as protected, due to their private licences. the remaining nanopublications are public and can therefore be published to the server network for public accessibility. the dataset of all public nanopublications can be found online. 4 we defined four corpus nanopublications for our case study: one for the text contained in the corpus and one for the annotations contained in the corpus, for each of the two existing corpora (parc and factbank). they contain basic information about the corpus and link to their content via an index nanopublication, as can be seen in this example (abbreviated here and below for readability): the word nanopublications point back to the text nanopublication and provide word-level information including the word string, the offset of this string with respect to the text, and the sentence number. they can also contain lemma and part-of-speech information. as this word level depends on tokenization, there can be differences in how different annotation corpora define word boundaries. for this reason, our approach allows for the generation of new word nanopublications on demand. this creates an identifier for the word based on the uri of the text nanopublication and the offset of the word, thereby assuring that words introduced several times by different annotation corpora get the same identifier and are therefore immediately interoperable. in our case, we have 6,362 word nanopublications defined from parc and 7,784 from factbank. this is an example of the former: sub:assertion { textoffset:3-9 a nif:offsetbasedstring, nif:word; nif:beginindex "3"^^xsd:int; nif:endindex "9"^^xsd:int; nif:anchorof "rogers"; nif:lemma "rogers"; olia:pos "nnp"; pvcp:hassentencenumber "0"^^xsd:int; pvcp:ispartoftext textnp:text . } the annotations can now link to these words. we have 136 annotation nanopublications for parc, that associate words with content, cue and source annotations, as can be seen in the example below: ## results in this section we analyze the interoperability challenges we faced and addressed with our approach and assess the extent to which we can automatically answer the questions we introduced above. ## discussion and conclusion nanopublications have been mostly used with scientific data, such as data from the biomedical domain @xcite . in this work, we show that linguistic corpora can also benefit from the fine-grained and provenance-aware structure of nanopublications. the collection of nanopublications presented here contains information from event annotated corpora. it is demonstrated that when these data is modelled in a homologous way, each unique corpus can be automatically merged in order to produce valuable data combinations that were not easily attainable prior to the merging. specifically, our dataset can provide attribution annotation insight about events from factbank. moreover, our nanopublications suggest the prospect of linguistic data fitting into the linked data ecosystem. during the dataset creation, we were able to reuse multiple existing linked data vocabularies. linguistic data becoming more linked would also allow it to be connected more easily with already existing linguistic linked data sources from llod. nevertheless, the data format of the original annotated corpora is extremely variable, which shows in the multiple textual challenges faced during production. while this project only focused on two corpora, there was inconsistency in annotation format not only between the corpora, but also within a corpus itself. thus, the conversion of existing linguistic corpora into a linked data scheme can expect tedious pre-processing efforts. even in our dataset, several documents needed to be excluded for the final version. another aspect that makes it challenging to fit linguistic corpora in the linked data ecosystem relates to copyright availability. for example, this caused us to only be able to represent part of the parc corpus. in this paper, interoperability issues in linguistic data, specifically event annotated corpora, are discussed and nanopublications are proposed as a solution to resolve them. when one set of annotation guidelines is used to produce annotations on one corpus, that same corpus might already have other annotations that could be useful for the researcher. however, currently it is very difficult for a researcher to know or retrieve the version or provenance of these existing annotations due to poor documentation and variable annotation formats. aspects of nanopublications that make them useful for annotated corpora are that they are able to be written in different formats, they can represent versioning, and they can track provenance. also, they follow llod principles of using uris for identification and rdf representation as output. above all, they seem useful for merging linguistic annotation data. a successful model for translating existing event corpora into nanopublications is significant not only for computational linguistics, but also for the field of linked data.