An annotation scheme for financial news in P ortuguese (2025)

Abstract: We present an annotation scheme designed to capture information related to the maintenance or change in the price of some goods (fuels, water, and vehicles) in news articles in Portuguese. The methodology we used involved adapting an existing annotation scheme, the Text2Story scheme (Silvano et al., 2021; Leal et al., 2022), which is based on different parts of ISO 24617 to capture the essential information for this project. Adaptations were needed to accommodate specific information, namely, information related to quantitative data and comparative relations that are abundant in this type of news. In this paper, we provide an overview of the annotation scheme, highlighting attributes and values of the entity and link structures specifically designed to capture financial information, as well as some problems we had to overcome in the process of building it and the rationale of some decisions behind its overall architecture.

## introduction corpora annotation is fundamental for theoretical linguistics research and for faster progress in improving natural language processing and information extraction tasks by providing training material and gold standards for model evaluation ( e.g., @xcite . in recent years, projects have been carried out to build annotation schemes and annotated corpora to capture the content of texts with more or less generic themes (e.g., groningen meaning bank (gmb) @xcite ; manually annotated sub-corpus (masc) @xcite ; georgetown university multilayer corpus (gum) @xcite ; for portuguese, @xcite . however, several studies have also emerged that seek to capture the content of texts from specific domains, such as the medical domain (cf., e.g., @xcite . these studies seek to overcome the particular difficulties of these domains, such as the specialized lexicon, which requires a more detailed ontological categorization of entities or specific links between these entities. the financial domain is one of these domains where efforts to build resources are scarce (cf., e.g., @xcite . in fact, there is a significant lack of annotated corpora to train models in this domain, which is not unrelated to the lack of explicitly designed annotation schemes to capture financial information. the project we present in this article aims to contribute to filling this gap. our general objective was to create an annotation scheme that captured information related to the maintenance or change in the price of some goods (fuels, water, and vehicles) in european portuguese (ep) news. the methodology we used involved adapting an existing annotation scheme, the text2story (t2s) scheme, to capture the essential information for this project. the reasons for choosing this methodology are related to the characteristics of the t2s scheme and the objectives of this annotation project, which are to capture the maintenance and variation of prices of some goods. on the one hand, the t2s scheme is a scheme created based on the iso 24617 standard @xcite , which guarantees interoperability, particularly if you want to add in the future distinct semantic layers to the annotation scheme, such as, for example, discourse relations. on the other hand, the t2s scheme was created to capture the narrative structure of news of generalist themes in ep and has already proven suitable for this purpose @xcite . thus, it was predictable that, despite having to make a certain number of changes to the t2s scheme to adapt it to the objectives of this specific project, the t2s scheme should be suitable, given that the type of text (news) and the language (ep) would be the same. in the following section, we present some previous work on annotating financial information in texts and, in particular, on annotating quantities. in the third section, we present the annotation scheme we built for annotating financial news and describe some problems we have encountered during the process. we also present some justifications for specific choices we have made while constructing this annotation scheme. we conclude with some final remarks and future work. ## related work reasoning based on numerical information is common in all human domains @xcite , particularly in scientific domains, in which one seeks to deduce scientific facts from premises that, in empirical sciences, are constructed based on quantitative data. for these reasons, in nlp, research on measurement expressions has focused on specific domains @xcite . for example, the medical domain is particularly interesting, as electronic health records contain much quantitative information (e.g., blood test results) relevant, for instance, to including patients in clinical trials. however, there are other interesting domains, such as the financial domain. in this field, research has focused more on the value of company shares and crude oil and, to a lesser extent, on the factors underlying the price variation of certain commodities @xcite . extracting these quantification expressions from texts in natural languages faces several challenges, starting with the format of these expressions @xcite . they are typically formed with a numerical value and a unit (which may or may not correspond to a standardized value). however, the numerical value can be presented in different ways (with letters or numbers); it can correspond to some vague form of quantification (e.g., 'a couple') or denote a numerical range (e.g., '3-5 g.'). the numerical value can correspond, for example, to a percentage relative to another quantification expression, which may be implicit in the text (e.g., 'the price of gasoline increased by 4%'). quantification expressions may also contain some modification, which alters their overall meaning (cf. '3 g.' vs. 'approx. 3 g.'). one problem found in some works related to the annotation of numerical expressions (e.g., @xcite is the fact that they only annotate cardinal quantifiers, leaving aside modifiers of these quantifiers: for example, in "at most 3%", they only annotate "3%" leaving aside the modifier "at most"; the same happens in "at least 2%". leaving aside the modifiers, they lose part of the nominal expressions' semantics. in this specific case, the distinction between right monotone increasing determiners ('at least') and right monotone decreasing determiners ('at most') foot_0 is lost (cf., e.g., @xcite . it is not just the identification of quantification expressions that is problematic. indeed, identifying how these quantification expressions measure entities or properties of entities (explicit or implicit in the texts) is also a problem in information extraction. for example, in 'gasoline costs 1.5 euros', the quantification expression is locating a characteristic of the entity denoted by "gasoline", its price per liter, on a numerical scale associated with a particular monetary unit. another problem is identifying price changes over time, as in 'gasoline costs 4 cents more than last week'. all these problems are further aggravated by a lack of uniformity in the terms used: in different projects, the same concept may correspond to different terms; conversely, the same term may have non-equivalent definitions in other projects (cf. @xcite . in this regard, the work carried out under iso 24617, parts 11 and 12, seeks to answer some of these questions. @xcite ) is a proposal to deal with quantification issues mainly related to the quantificational information of nominal expressions but also of eventualities expressions and the scope relations in which these expressions are involved. as for iso @xcite , it deals with aspects related to measurable quantitative information, that is, with the standardization of expressions involving a quantity n and a unit u, as in 'two meters'. also noteworthy is the work of @xcite , who propose a semantic tagset for use in a new nlp task to encode information that better characterizes lexical semantics than pos tags 2 . these tags describe the semantic contribution of particular words or punctuation marks concerning the meaning of the whole expression and are grouped into 13 meta-tags. for example, the att (attribute) meta-tag includes the quc (quantity of concrete) tag, which applies to words such as 'two', and the nam (named entity) meta-tag includes the uom (unit of measurement) tag, which applies to words such as 'euro' or 'percent'. datasets available to train models specifically with quantitative information are not abundant, particularly full-text datasets. quantitative information is particularly relevant in texts from specialized domains, so these domains, such as medicine or finance, are necessary for this type of annotation. however, the question of finding suitable annotators for this type of task is also pertinent: annotators must have grammatical knowledge and, in some cases, knowledge of the specific domain (for instance, in cases of quantities given relative to a standard; cf. @xcite . projects have sought to use llms as annotators to overcome this difficulty, given that these models have proven effective in annotating general domain datasets. @xcite show that llms are a possible alternative to non-expert crowd workers for domain-specific tasks. however, they do not surpass domain-specific human experts. another problem with datasets in the financial domain is that they often consist only of news headlines, and the annotation aims to perform sentiment analysis on stock prices. there are a few publicly available datasets with information about commodity news. @xcite present one of these datasets, which is a dataset consisting of 11,412 news headlines about gold. this dataset was manually annotated with various information, namely whether the price is attributed to the past or the future ("past/future price information") and whether this value corresponds to an increasing, decreasing, or maintenance trend ("price up/constant/down"). regarding news annotation work on commodities, @xcite report that datasets of this type are scarce, and the authors assume that their dataset may be the only annotated corpus. this is a dataset of 425 news articles about crude oil in english, manually annotated by undergraduate students from a school of business. this dataset has some similarities to the one we developed in this proposal to our attention. to sum up, identifying quantification expressions is a complex task, but one that is fundamental in several areas of research (cf. @xcite for a survey on measurement extraction in nlp tasks). in our project, we are particularly interested in extracting the value attributed to specific products over time: fuels (gasoline, diesel), motor vehicles, and essential goods (water, electricity). we will present a corpus of newspaper articles about finances, given that these texts often present numeric information representing different aspects of the situations they describe: in the case that interests us, the price of commodities @xcite . ## description of the scheme for annotating commodities price information the scheme we created includes the following: most of the content of this annotation scheme is based on parts of the iso standard iso24617, language resource management -semantic annotation framework: part 1: time and events (iso-24617-1, 2012); part 4: semantic roles (iso-24617-4, 2014); part 7: spatial information (iso-24617-7, 2020); and part 9: reference annotation framework (iso-24617-9, 2019). however, it was necessary to create some attributes and links to capture the information relevant to this annotation project, which will be detailed below. although a part of iso deals with quantification, iso 24617 -part 12: quantification (iso-24617-12, 2024), we decided not to include it in this project. there are several reasons for this. for example, the expressive power of iso 24617 -12, notably in the annotation of quantificational information of nominal expressions and in the scope relations between nominal expressions and between these expressions and eventualities or other operators, such as negation, would not be used because this kind of information does not appear in the news that constitute our corpus. so, although iso 24671-12 is quite expressive, our project did not require the level of detail proposed in this part of the iso. we argue that the simplicity of the annotation scheme is crucial if one wants to recruit annotators without specialized linguistic knowledge. using iso 24617-12 also poses some problems. one is that this part of the standard does not cover some of the expressions we had to annotate, namely, the quantification expressions of the "non-exact" type. another problem is that many of the eventualities in the annotated news are expressed by nominal expressions with adjectives expressing quantification. neither iso 24617-12, for quantification, nor iso 24617-9, for referential annotation, suggests ways to deal with these adjectival expressions that express some form of quantification over eventualities expressed by nouns. examples (1) and (2) illustrate these cases. these sentences contain nominal expressions that, semantically, are equivalent to the sentences in (3) and ( 4 ), with explicit quantification within the verb phrase. the news annotations were performed in brat @xcite . the manual was built incrementally, following the mama cycle @xcite , taking the text2story scheme as a starting point. a phd student in linguistics annotated a set of news items and identified problems in the annotation process. in a meeting with two senior linguistics researchers, these problems were discussed, and solutions were proposed. the student revised the annotation according to these solutions, and in the following meeting, the new results were analyzed. if the problems persisted, new solutions were proposed. if the problems were solved, the student annotated a new set of news items. this process was repeated cyclically until the entire set of news items was annotated, and no problems were left in the annotation. finally, the news annotations (@xmath0. ## concluding remarks the annotation of information about quantities is a topic that still requires further study, both in terms of annotation schemes that adequately capture the various nuances that quantification expressions can have in natural languages and in terms of annotated corpora that can be used to train models or as gold standards in evaluation tasks. in this article, we seek to contribute to the discussion on annotation schemes and present a new scheme to capture information related to the rise, fall, or maintenance of commodities prices in news articles. to that end, we propose an extension of the text2story scheme, which, in turn, was built by combining four parts of iso 24617 (parts 1, 4, 7, and 9). the new scheme contains new attributes and values specially designed to capture the quantificational information typical of news in the financial domain. this new scheme can also be extended to capture other types of information. in the future, we plan to include other iso resources, such as the entire semantic role array of iso 24617-4, and other parts, such as iso 24617-8 (iso, 2016), using the discourse relations framework to analyze the underlying reasons for price changes. another line of research is this scheme's application (with the necessary adaptations) to other domains with abundant quantificational information, such as electronic health records. finally, formalizing the semantics of the proposed annotation scheme is still missing.