Table 3 - uploaded by Norbert Schlüter
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The 10 most frequent adverbials co-occurring with the present perfect in American English (BROWN EP and BROWN FT)
Source publication
Temporal relations in English are expressed by both verbal patterns and non-verbal elements, such as temporal adverbials. Most grammatical descriptions referring to temporal adverbials in this function, however, are not derived from empirical investigations but from intuitive impressions. The aim of this paper is to present results of a corpus-base...
Context in source publication
Context 1
... groups are in + tmp NP (in the past year, in the last 18 months) and (ever) since (+ tmp NP/CL) 6 , which contains temporal adverbials like the following: since, ever since, since last May, since then, since you left, ever since you were a girl. The following tables list the ten most frequent temporal adverbials/groups of adverbials co-occurring with the present perfect in British English (Table 2) and American English (Table 3). The two tables show that the ten most frequent temporal adverbials co-occurring with the present perfect in British English are identical to the ten most frequent temporal adverbials co-occurring with the present perfect in American English, even if their order differs slightly. ...
Citations
... Prior work [1,2] has considered rule-based temporal inference by using temporal conjunctions and prepositions. Schluter et al. [23] list temporal signals in English expressions and compare their frequencies in British and US English. Derczynski et al. [5] suggest that, a large portion of temporal signal expressions has a SBAR-TMP or PP-TMP subtree structure, where SBAR is the mark for clause that is introduced by a (possibly empty) subordinating conjunction, PP is the label for the prepositional phrase and the suffix -TMP is a functional tag that indicates the existence of temporal adverbials. ...
We address the problem of video moment localization with natural language, i.e. localizing a video segment described by a natural language sentence. While most prior work focuses on grounding the query as a whole, temporal dependencies and reasoning between events within the text are not fully considered. In this paper, we propose a novel Temporal Compositional Modular Network (TCMN) where a tree attention network first automatically decomposes a sentence into three descriptions with respect to the main event, context event and temporal signal. Two modules are then utilized to measure the visual similarity and location similarity between each segment and the decomposed descriptions. Moreover, since the main event and context event may rely on different modalities (RGB or optical flow), we use late fusion to form an ensemble of four models, where each model is independently trained by one combination of the visual input. Experiments show that our model outperforms the state-of-the-art methods on the TEMPO dataset.
... Prior work [1,2] has considered rule-based temporal inference by using temporal conjunctions and prepositions. Schluter et al. [23] list temporal signals in English expressions and compare their frequencies in British and US English. Derczynski et al. [5] suggest that, a large portion of temporal signal expressions has a SBAR-TMP or PP-TMP subtree structure, where SBAR is the mark for clause that is introduced by a (possibly empty) subordinating conjunction, PP is the label for the prepositional phrase and the suffix -TMP is a functional tag that indicates the existence of temporal adverbials. ...
We address the problem of video moment localization with natural language, i.e. localizing a video segment described by a natural language sentence. While most prior work focuses on grounding the query as a whole, temporal dependencies and reasoning between events within the text are not fully considered. In this paper, we propose a novel Temporal Compositional Modular Network (TCMN) where a tree attention network first automatically decomposes a sentence into three descriptions with respect to the main event, context event and temporal signal. Two modules are then utilized to measure the visual similarity and location similarity between each segment and the decomposed descriptions. Moreover, since the main event and context event may rely on different modalities (RGB or optical flow), we use late fusion to form an ensemble of four models, where each model is independently trained by one combination of the visual input. Experiments show that our model outperforms the state-of-the-art methods on the TEMPO dataset.
... Kranich (2010: 140) argues that, in BrE, perfect progressives occur regularly with adverbials indicating duration, with the effect that the long duration of the situation is brought into focus. Schlüter (2002) investigates the use of temporal adverbials with the present perfect 115 in five corpora representing BrE and AmE, and finds a very stable picture of approximately a third of all present perfect forms being accompanied by a temporal adverbial. In the present study, approximately 40% of all perfect progressives co-occur with a temporal adverbial, while the corresponding figure for all progressive forms is less than 20%. ...
... In Schlüter's (2002) data, for [x amount of time] is the third most common temporal adverbial co-occurring with the present perfect. The most common temporal adverbial in Schlüter's data is (ever) since (NP), which in this study is the second most common temporal adverbial with the perfect progressive. ...
... The registers included inBiber et al. (1999) are conversation, fiction, news and academic.115 Schlüter (2002) does not provide information on whether the present perfect progressive is included in the present perfect paradigm of the study. ...
You'll find the thesis here: https://urn.fi/URN:ISBN:978-951-44-9636-3
... However, this work is purely theoretical and not a corpus-based study. Schlüter (2001) identifies signal expressions used with the present perfect and compares their frequency in British and US English . Vlach (1993) presents a semantic framework that deals with duratives when used as signal modifiers (see Section 2.1.). ...
Automatic temporal ordering of events described in discourse has been of
great interest in recent years. Event orderings are conveyed in text via va
rious linguistic mechanisms including the use of expressions such as "before",
"after" or "during" that explicitly assert a temporal relation -- temporal
signals. In this paper, we investigate the role of temporal signals in temporal
relation extraction and provide a quantitative analysis of these expres sions
in the TimeBank annotated corpus.
... Grammar books do not only contain explanations on the use of tenses but regularly refer to temporal adverbials which co-occur with the respective verb pattern. After establishing the most frequent temporal adverbials co-occurring with the present perfect (Schlüter 2001(Schlüter , 2002 this paper investigates patterns of co-occurrences with other tense forms. On the basis of corpus evidence such patterns were exemplarily identified for already, always, and for. ...
Grammar books do not only contain explanations on the use of tenses but regularly refer to temporal adverbials which co-occur with the respective verb pattern. After establishing the most frequent temporal adverbials co-occurring with the present perfect (Schlüter 2001, 2002) this paper investigates patterns of co-occurrences with other tense forms. On the basis of corpus evidence such patterns were exemplarily identified for already, always, and for. The findings suggest that even though the adverbials co-occur frequently with the present perfect there are frequent patterns of co-occurrences with several other tense forms such as the simple present and simple past.
In Chap. 4, we saw that a proportion of difficult temporal relations were associated with a particular separate word or phrase that described the temporal relation type – a temporal signal.
