Bridging Resolution: A Survey of the State of the Art (2020)

Abstract: Bridging reference resolution is an anaphora resolution task that is arguably more challenging and less studied than entity coreference resolution. Given that significant progress has been made on coreference resolution in recent years, we believe that bridging resolution will receive increasing attention in the NLP community. Nevertheless, progress on bridging resolution is currently hampered in part by the scarcity of large annotated corpora for model training as well as the lack of standardized evaluation protocols. This paper presents a survey of the current state of research on bridging reference resolution and discusses future research directions.

## introduction bridging resolution is an anaphora resolution task that involves identifying and resolving bridging/associative anaphors, which are anaphoric references to non-identical associated antecedents. to better understand the difficulty of the task, consider the following sentences: even if baseball triggers losses at cbs -and he doesn't think it will -"i'd rather see the games on our air than on nbc and abc," he says. in this example, a bridging link exists between the anaphor the games and its antecedent baseball, as the definite description cannot be interpreted correctly unless it is associated with baseball. bridging anaphora resolution is arguably more difficult than entity coreference resolution, the task of determining which entity mentions in a text refer to the same real-world entity. for entity coreference resolution, there are well-defined linguistic constraints at the grammatical (e.g., gender and number agreement), syntactic (e.g., binding theory), semantic (e.g., semantic class agreement), and discourse (e.g., centering) levels. oftentimes, the antecedent of an anaphor can be identified by comparing its lexical similarity with the anaphor. in contrast, there are typically no clear syntactic or other surface clues for identifying the antecedent of a bridging anaphor. it is not uncommon that resolution requires the use of context as well as commonsense inference. furthermore, while antecedents in entity coreference are noun phrases (nps), antecedents in bridging can also be non-nps such as verb phrases (vps) or clauses, which considerably increase the possible number of candidate antecedents for each anaphor. bridging resolution is comparatively less studied than entity coreference resolution. progress on bridging resolution is currently hampered in part by the scarcity of large annotated corpora for model training as well as the lack of standardized evaluation protocols. more specifically, while there are a few bridging corpora that are used more extensively than the others for evaluation purposes, many of which do not have standard train-test partitions. moreover, these corpora were annotated with somewhat different definitions of bridging, so good performance on one corpus does not necessarily translate to good performance on another. worse still, resolvers were evaluated under different settings. for instance, different researchers employ different, sometimes undocumented strategies for filtering bridging anaphors and candidate antecedents, while others employ gold annotations (e.g., syntactic parses, coreference) for feature computation. above all, many of the implementations of bridging resolvers have not been as significant advances have been made on entity coreference resolution, we believe that bridging reference resolution will gain increasing attention in the years to come. our goal in this paper is to provide a timely survey of the current state of research on bridging anaphora resolution. ## task definition: some historical perspectives the definition of bridging has evolved over the years, particularly with respect to (1) the types of relations bridging should cover, and (2) the types of linguistic expressions that can serve as bridging anaphors. in this section, we take a closer look at these two issues. first, what types of relations should bridging cover? as a linguistic phenomenon, bridging has been studied extensively by linguists (e.g., @xcite , @xcite , @xcite ). @xcite , who started this area of research, introduced a broad concept of bridging that includes coreference (i.e., the identity relation). coreference, however, is gradually being excluded from bridging over time. for instance, while some early studies still included the difficult cases of coreference where two coreferent mentions do not share the same head as bridging @xcite @xcite 1 , most of the recent studies focus on non-identity cases of bridging, which is the closest to @xcite concept of associative anaphora. among the non-identity relations, bridging covers various types of semantic relations. while early studies typically restrict themselves to predefined relations such as part-of, subset, set membership, and possession relations @xcite , recent studies claim that bridging is a diverse phenomenon that cannot be simply captured with a limited set of predefined relations @xcite . second, what types of linguistic expressions can serve as bridging anaphors? many traditional studies @xcite @xcite limited bridging anaphors to definite expressions, excluding indefinite expressions since they generally introduce new information that can be interpreted without the discourse context. however, @xcite claimed that bridging anaphors can also be indefinite because these indefinite expressions can have semantic relations with preceding expressions. recent studies therefore allow both definite and indefinite expressions to serve as bridging anaphors @xcite @xcite . ## corpora this section provides an overview of existing corpora used for bridging research, with a focus on four widely-used english corpora, namely isnotes (composed of 50 wsj articles in ontonotes) @xcite , bashi (the bridging anaphors hand-annotated inventory, composed of another 50 wsj articles in ontonotes) @xcite , arrau (composed of articles from four domains, rst, gnome, pear, and trains) @xcite , and scicorp (the scientific corpus, composed of scientific articles from computational linguistics and genetics) @xcite . several non-english bridging corpora exist. dirndl @xcite , semdok @xcite , and grain @xcite are in german. dede @xcite and parole @xcite are in french. caselli/prodanof @xcite and italian live memories corpus @xcite are in italian. prague dependency treebank @xcite is in czech. cess-ece @xcite is in spanish. corea @xcite is in dutch. the sasano-kurohashi corpus @xcite is in japanese. rugenbridge @xcite is in russian. parallel bridging corpora are also available. for instance, copenhagen dependency treebank is a parallel corpus involving danish, english, italian, german, and spanish @xcite , and corefpro is a parallel corpus involving german, english, and russian @xcite . while not widely used, gum is an ever-expanding english corpus annotated with bridging links by students at georgetown university @xcite . ## evaluation issues as mentioned before, an issue surrounding bridging resolution research concerns the lack of a standardized evaluation protocol. in this section, we take a look at current evaluation practices. evaluation settings. bridging resolvers operate in one of three settings. in end-to-end bridging resolution, a system is given a raw document as input. the goal is to identify the bridging anaphors (a subtask known as bridging recognition) and resolve each of them to its antecedent. since this setting is considered very challenging, none of the existing bridging resolvers are evaluated in an end-to-end fashion. in full bridging resolution, a system is given as input not only a document but also the gold (i.e., hand-annotated) mentions in the document. the goal is to identify the subset of the gold mentions that are bridging anaphors and resolve them to their antecedents, which are also chosen from the gold mentions. in principle, gold mentions are mentions that can participate in a bridging relation. in practice, gold mentions are typically much smaller than the set of possible mentions. since full bridging resolution constrains the selection of anaphors and antecedents to those that are gold mentions, it is less challenging than the end-to-end setting. gold mentions are defined slightly differently in different corpora. in isnotes, gold mentions include nps, possessive nouns/pronouns, premodifiers, and verbs. in bashi, gold mentions are assumed to be all and only those nps that can be extracted from gold parse trees. in arrau, gold mentions include all nps, possessive pronouns, and a subset of premodifiers. in scicorp, gold mentions are definite nps, which include definite descriptions, named entities, and pronouns. finally, in bridging resolution, a system is given as input not only a document and the gold mentions it contains, but also the gold anaphors. the goal is to resolve each gold anaphor to its antecedent, which is chosen from the given set of gold mentions. this setting is the least challenging of the three, as it focuses solely on resolution and does not require bridging anaphors to be identified. evaluation metrics. for full bridging resolution, results are reported for both recognition and resolution in terms of precision, recall, and f-score. for recognition, recall is defined as the fraction of gold anaphors that are correctly identified, whereas precision is defined as the fraction of anaphors identified by the system that are correct. for resolution, recall and precision can be defined in a similar fashion. for bridging resolution, since gold anaphors are given, results are reported in terms of resolution accuracy, which is the fraction of gold anaphors that are correctly resolved. ## the state of the art to better understand the state of the art, we show the best results achieved on bridging resolution and full bridging resolution by different approaches on three commonly used datasets (isnotes, bashi, and arrau rst) in tables 5 and 6 respectively. note that (1) these results are taken verbatim from the respective papers, and (2) not all of them are directly comparable, as some rely on gold coreference chains to compute cluster-level features or perform anaphor filtering. as we can see in ## concluding remarks we have presented a survey of the current state of research on bridging resolution, a task that is far from being solved. given that significant advances have been made on coreference resolution recently, we believe that bridging resolution will be the anaphora resolution task that will receive increasing attention in the near future. we conclude this paper with several recommendations on future research directions.