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Proceedings of the Third Italian Conference on Computational Linguistics CLiC-it 2016

Anna Corazza
Simonetta Montemagni
Giovanni Semeraro

Enrichring the Ita-TimeBank with Narrative Containers

Alice Bracchi, Tommaso Caselli et Irina Prodanof


This paper reports on an annotation experiment to enrich an existing temporally annotated corpus of Italian news articles with Narrative Containers, annotation devices representing temporal windows in text and marking up very informative temporal relations between temporal entities. The annotation has shown that the distribution of Narrative Containers is sensitive to the text genre and may be used to facilitate the creation of informative timelines.

Questo lavoro illustra i risultati di un esperimento di annotazione per l’identificazione di Contenitori Narrativi, ovvero marcatori di “finestre” temporali in un testo, come strategia per arricchire un corpus di articoli di quotidiano in lingua italiana, già annotato con informazioni temporali. L’annotazione ha mostrato che la distribuzione dei Contenitori Narrativi è legata al genere testuale e puo essere usata per facilitare la creazione di linee temporali di eventi più informative.

Texte intégral

1 Introduction

1Research in Temporal Processing has seen an increasing interest thanks to the availability of annotation schemes and corpora in multiple languages (Pustejovsky et al., 2003; Bittar et al., 2011; Caselli et al., 2011; Saurı and Badia, 2012), and the organization of evaluation campaigns (TempEval (Verhagen et al., 2007; Verhagen et al., 2010; UzZaman et al., 2013), Clinical TempEval (Bethard et al., 2015; Bethard et al., 2016), Cross-Document TimeLine (Minard et al., 2015), Temporal QA (Llorens et al., 2015)), and EVENTI (Caselli et al., 2014)). This has established best practices, common evaluation frameworks, international standards (e.g. ISOTimeML (Pustejovsky et al., 2010)), and approaches to solve such a complex task. However, the expression of time in text/discourse is by no means obvious and the automatic extraction of timelines is not a solved task yet. One of the limits of current annotation frameworks and corpora relies mainly in the sparseness of the available temporal relations and in the fine-grained values used to classify the temporal links. For instance, in the TempEval-3 corpus the ratio between temporal relations and event plus temporal expressions is 0.8 (Bethard et al., 2014) for 13 temporal values. In the EVENTI corpus, the ratio is even smaller, only 0.19 for 13 temporal values1. Furthermore, in some cases annotation guidelines are not informative enough concerning what types of temporal links to annotate, or they force the annotation of temporal relations between pairs of events when they should not be annotated. Attempts to overcome these limits have focused on three main strategies: i.) annotating particular sets of temporal relations (Kolomiyets et al., 2012); ii.) elaborating detailed annotation guidelines for each kind of temporal relations (event-temporal expression pairs, event-event pairs, and temporal expression-temporal expressions pairs); and iii.) developing densely connected temporal graphs, where all valid relations among the temporal entities (events and temporal expressions) are marked up, including inferred relations based on transitive properties of the temporal relations (e.g. if event A is BEFORE event B and event B IS INCLUDED in event C, then event A is BEFORE event C) (Bethard et al., 2014). We consider these solution as partial as they are not able to address the issue of identifying and extracting informative timelines, i.e. a set of maximally informative temporal links where relevant events in a text/discourse are correctly anchored to time, and then chronologically ordered. This paper reports on the first annotation effort to enrich existing resources for Temporal Processing in Italian by adopting a document-level approach rather than a sentence-level one. Following the proposal of Narrative Containers (NCs) (Pustejovsky and Stubbs, 2011), as embedding intervals where events occur, we developed an annotation scheme for their identification on the EVENTI corpus (Caselli et al., 2014)2, as a strategy to increase the informativeness of the existing annotations and, possibly, improve systems’s temporal awareness.

2The remainder of this paper is structured as follows: the EVENTI corpus will be shortly introduced in Section 2, with a particular emphasis on the available temporal relations. Section 3 will present the notion of Narrative Container and the proposed annotation scheme. In Section 4 the results of a pilot annotation on the EVENTI dataset will be reported. Finally, conclusion, future work, and a pointer to the annotated data and guidelines will be reported in Section 5.

2 Temporal Relations in the EVENTI Corpus

3The EVENTI corpus, released in the context of the EVALITA 20143 workshop, consists of 3 datasets: the Main task training data, the Main task test data, and the Pilot task test data. The corpus has been annotated with a simplified version of the It-TimeML Annotation Guidelines (Caselli et al., 2011), an adapted version to Italian of the TimeML Guidelines. Four tags have been used to annotate the data: EVENT, TIMEX3, SIGNAL, and TLINK.

4The EVENT tag is used to annotate all lexical items which may realize an event mention. It includes verbs, nouns, adjectives, and prepositional phr ases. The tag is enriched with 8 attributes expressing tense, (grammatical) aspect, part-of-speech, mood, modality, verb form, TimeML class, and polarity.

5The TIMEX3 tag is used for the annotation of temporal expressions (timexes), expressing the type, the value and whether the timex is absolute or relative (e.g. “2015-05-18” vs. “yesterday”[ieri]).

6The SIGNAL tag is employed to mark any linguistic elements, such as prepositions (e.g. in [in]), adverbs (e.g. before [prima]), or conjunctions (e.g. when [quando]), which support the identification and classification of a temporal relation between target entities (e.g. events and timexes).

7Finally, the TLINK tag is used to annotate temporal relations. In the EVENTI task, the subset of possible temporal relations has been restricted to three subtypes of intra-sentence relations, namely: i.) pairs of syntactic main events in the same sentence; ii.) pairs of syntactic main event and subordinate event in the same sentence; and iii.) pairs of event and timexes. All 13 temporal relation values from It-TimeML (BEFORE, AFTER, IS_INCLUDED, INCLUDES, SIMULTANEOUS, I(MMEDIATELY)_AFTER, I(MMEDIATELY)_BEFORE, IDENTITY, MEASURE, BEGINS, ENDS, BEGUN_BY and ENDED_BY) have been used.

8The Main task datasets, which have been enriched with Narrative Containers, add up to 130,279 tokens, divided into 103,593 tokens for training and 26,686 for test. They contain 21,633 EVENTs (17,835 in training and 3,798 in test), 3,359 TIMEX3 (2,753 in training and 624 in test), 1,163 SIGNALs (923 in training and 231 in test), and 4,561 TLINKs (3,500 in training and 1,061 in test).

3 Adding Narrative Containers to News Articles

9The notion of Narrative Container (NC) was first introduced by Pustejovsky and Stubbs (2011) to deal with some aspects of Temporal Processing, such as sensitivity to the text genre and interaction with discourse relations, not addressed in the TimeML Guidelines nor in the TimeBank corpus. NCs were proposed as a temporal window, providing left and right boundaries, to when events not anchored to timexes could have happened, thus overcoming issues related to linking of events with the Document Creation Time (DCT), i.e. when a text was written or published. In particular, standard TimeML markup imposes that all events have a link with the DCT but fail to specify that each event should also be annotating to its actual temporal anchor, i.e. to its moment of occurrence. As reported in Pustejovsky and Stubbs (2011), in example 1, TimeML guidelines will order both event mentions, e1 and e2, to the DCT with a BEFORE relation, anchor e1 to the timex “yesterday” (t) but will fail to provide the anchoring of e2:


1. The bomb explodede1yesterdayt20110909 and killede2 three people. [DCT=2011-09-10]


10A further justification to the introduction of NCs is related to the different informational status of temporal relations. Assuming the informativeness of a temporal link as a function of the information contained in the individual links and their closure, an anchoring relation, that is a relation between a timex and an event explicitly stating when the event occurred as the one between e1 and timex “yesterday” in example 1 (i.e. a temporal value of INCLUDES or IS INCLUDED), is assumed to be more informative than an ordering relations, i.e. a precedence relation between two events.

11To the best of our knowledge, the only corpus which extensively adopts the notion of NC and has available annotated data is the THYME corpus of clinical narratives (Styler IV et al., 2014). Our task is the first attempt at tackling temporal containment annotation over news articles in Italian.

12A NC enables an accurate reproduction of the way events in text cluster around temporal reference points, explicitly or implicitly realized in the document, as the narration unfolds. NC relations are thus anchoring relations between pairs of events or events and temporal expressions. They are marked with an additional link tag, i.e. CONTAINS, to distinguish them from standard TLINKs. Each NC relation admits two components: i.) the narrative anchor, i.e. an element pointing to a specific temporal dimension shared by other events or timexes within the text; and ii.) the anchored element(s), i.e. events which satisfy the anchorability requirements (see Section 3.1 for details) and participate in an NC relation. Timex anchors are chosen on a transparency basis (i.e. granularity and nature of the timex), whereas Event anchors are chosen according to their relevance and salience for the timeline.

13Two sub-types of NCs can be identified:

  • Temporal Containers (TCs): they correspond to the timexes in the text which clearly anchor the events in analysis on a timeline; the relation can hold both at intraand intersentence level. Example 2 from our annotated corpus shows a timex (2001) and the events it anchors (e1–e4):

2. [...] la Sonata composta[e1] nel 2001[TCanchor], il cui primo esecutore fu[e2] lo stesso Lucchesini. In questa esecuzione[e3] si ritrovavano[e4] già tutte le doti musicali di Lucchesini [...].

  • Event Containers (ECs): they correspond to event mentions which function as a temporal anchor for other event mentions. ECs can be useful in cases where no anchoring timex is available or to model event-subevent relations. Example 3 shows a sentence with no explicit temporal expression, where the anchoring of events (e1–e3) is possible only with respect to the event (ricognizione).

3. [...] Durante la ricognizione[ECanchor], il tenente ha dato disposizioni[e1] per il presidio, e nella fase[e2] iniziale ha ordinato[e3] ai sottoposti di fare rapporto al campo base.

14Figure 1 serves as a visual representation of the NC as annotated in example 2. By means of NCs, a document timeline will result in an ordered succession of NCs rather than of isolated events. This is the NC resulting from the following sentence, taken from the annotated corpus.

Figure 1: Visual representation of a NC for the sentence in Example 2.

Figure 1: Visual representation of a NC for the sentence in Example 2.

15Naturally, the NC represented here is only a visual aid picturing the conceptual outcome of applying CONTAINS relations between the anchor (here, the TIMEX3 2001) and anchored elements (here, EVENTs composta, fu, esecuzione, and ritrovavano)

3.1 Event Anchorability Requirements

16The set of events which can be anchored has been restricted to factual events. The identification of eligible anchorable events has been manually conducted at this stage of the annotation. We adopted the definition of factuality as proposed in the Fact-Bank (Saurí, 2008) and which is based on the double axis of polarity (positive vs. negative) and certainty. For the sake of our annotation task, only positive and certain events can be anchored. Events in the future were generally not annotated as they normally do not have a certain status. However, those events with an established schedule (e.g. deadlines, meetings), or whose future temporal window is assumed to be certain, such as festivities, have been annotated in anchoring relations as well.

17We excluded all events which are presented as subjective (i.e. judgements, opinions). In example 4, esplosione is a factual event and was anchored as such, whereas sbagliato describes it through the grid of the writer’s judgement, who states that the explosion was a mistake, and thus not anchored.

4. L’esplosionee1 è avvenuta a mezzanotte di lunedì [...]. Insomma, gli attentatori hanno sbagliatoe2 obiettivo.

18Finally, generic events, i.e. events which acquire some kind of attributive value towards discourse participants, expressing persistent properties or reiterated, habitual activities, were not anchored.

4 The EVENTI-NC Corpus

19The EVENTI-NC corpus includes documents from both the training and the test sections of the Main task of the EVENTI corpus. It includes 58 annotated articles, for a total of 24.259 tokens, covering roughly 11% of the EVENTI corpus; Table 1 shows the number of EVENTs and TIMEX3 involved in our annotation.

20Table 2 reports the number of annotated containers in our corpus, and their distribution according to their type. TCs make up for almost 63% of the total number of NCs, against the 37% of ECs. It is interesting to notice that 11.8% of TCs is realized by empty TIMEX3s, i.e. temporal expressions which do not correspond to lexical items but can be inferred and which are necessary to for assigning a correct value to a timex.

Table 1: Overview of corpus statistics.

General EVENTI-NC statistics



Annotated articles


EVENT markables


TIMEX3 markables


Table 2: Distribution of Narrative Containers in the corpus

Annotated NCs





Verbal anchors



Nominal anchors



Total EC n.







Empty TIMEX3s



Total TC n.



Total NC n.


4.1 Distribution of Narrative Containers anchors

21We conducted an in-depth analysis of the NC anchors following two parameters: i.) the properties of NC anchors on their own; and ii.) the sensitivity to the document genre, i.e. the news domain, on the line of Pustejovsky and Stubbs (2011).

  • 4 adige20040709 id405401.txt

22Concerning the first parameter, we first investigated the incidence of verbal anchors as opposed to nominal anchors. Whereas there appear to be no tendency towards verb or nouns being more likely to anchor other events, it is interesting to take a look within these categories. Out of all the verbal anchors, 42.9% are reporting verbs or verbs employed in a declarative context. We observed that there is a preference for ECs to correspond to the the event with the highest degree of topicality in the article, or the most important event (climax event). For example, one article4 reports on President Clinton’s surgery in 2004: the largest EC in the document is anchored by intervento (surgery), with a total of 12 anchored items.

23Sensitivity to text genre can be easily observed with TC anchors. 25% of them anchor events in a timespan that can be measured as 1 day with respect to the DCT. Anchors for these containers are mostly represented by non absolute temporal expressions, such as temporal adverbs (e.g. “ieri” [yesterday], “domani” [tomorrow], among others) and by the DCT itself, which represents 11% of the TC anchors.

24Genre-sensitivity might also be the factor behind the average number of NCs in the corpus. The documents have an average of 5.17 NCs, and even for more lengthy articles, the textual anchors were rarely more than 7. The average of 5.17 NCs/article might be due to the fact that newspaper articles usually refer to a limited number of facts, whose core is usually made of a handful of recent happenings; whereas the fluctuating relationship between length and NC number usually depends both on the content of the article and on the granularity of the selected NC.

5 Conclusion

25This paper reports on a first proposal of an annotation scheme and accompanying annotated data for NCs in Italian news articles. The NC annotation is an additional layer on top of already available data for Temporal Processing in Italian. It addresses pending issues (e.g. the annotation of the temporal relations between event and the Document Creation Time) and increases the informativeness of the document timelines. Overall, we observed that there is a preference for NC to be realized by timexes in a limited time span. However, NCs may also be realised by events. In this case, nouns and verbs have a similar distribution with a preference for events which have a central role in the news or facilitate the clustering of the information (e.g. reporting events). Such a behaviour is different with respect to clinical narratives where nominal events are more frequently selected as NC (Bethard et al., 2016). This suggests that different text genres present different ways of organizing events on a timeline. The introduction of the factuality parameter to select the anchoring events is a strategy to clean timelines and to move Temporal Processing from a single document to a cross-document task.

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26Future work will aim at assessing the reliability of the proposed scheme via an inter-annotator agreement study and at completing the annotation of the entire EVENTI corpus. Finally, the annotated data and guidelines are publicly available5 to encourage additional testing and experiments.


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1 The smaller ratio for the Italian data is also due to specific restrictions on the annotation of the temporal relations as reported in the EVENTI Annotation Guidelines and explained in Section 2.



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Titre Figure 1: Visual representation of a NC for the sentence in Example 2.
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