A return value of 1 indicates that Full-Text Search and Semantic Search are installed; a return value of 0 indicates that they are not installed. These two optional features of SQL Server are installed together. Semantic Search has an additional external dependency that is called the semantic language statistics database.
This database contains the statistical language models required by semantic search. A single semantic language statistics database contains the language models for all the languages that are supported for semantic indexing. Query the catalog view sys. If the semantic language statistics database is installed and registered for the instance, then the query results contain a single row of information about the database.
The semantic language statistics database is not installed by the SQL Server setup program. To set up the Semantic Language Statistics database as a prerequisite for semantic indexing, do the following things:. Locate the semantic language statistics database on the SQL Server installation media or download it from the Web.
Locate the Windows installer package named SemanticLanguageDatabase. Run the SemanticLanguageDatabase. You can optionally change the destination directory.
By default, the installer extracts the files to a folder named Microsoft Semantic Language Database in the Program Files folder.
The answer to this question is closely dependent on the answer to the so-called globalism-localism dispute. Gricean pragmatics is not the only approach in which defaults are discussed.
Defaults and nonmonotonic reasoning are also well entrenched in computational linguistics. Such defaults can be built into standard logic:. But the resulting logic will become nonmonotonic because there are default rules and default operators in the language. The literature on the topic is vast and is best considered as a separate topic from our current concern see e.
SDRT is an offshoot of Discourse Representation Theory, a dynamic semantic approach to meaning according to which meaning arises incrementally through context change. In SDRT, defaults are regarded as highly probable routes that an interpretation of a sentence may take in a particular situation of discourse. There are rules of discourse, so-called rhetorical structure rules , that produce such default interpretations. These rules spell out the overall assumption that discourse is coherent and that this coherence can be further elaborated on by proposing a set of regularities.
For example, two events represented as two consecutive utterances are presumed to stand in the relation of Narration , where the event described in the first utterance precedes the one from the second utterance.
If the second utterance describes a state, then it stands in the relation of Background to the first one. There are many other types of such relations, among them Explanation and Elaboration. Axioms prevent a relation from being of two incompatible types at the same time. The relations between states and events are computed as strong probabilities, in the process called defeasible reasoning. The inference normally , but not always , obtains: ceteris paribus, the relation predicted by the law obtains, but in certain circumstances it may not.
It is also nonmonotonic in that the relation may disappear with the growth of information. In other words, they stand for the meanings of two consecutive utterances.
The main strength of this approach is that it is fully formalized and it allows for computational modelling of discourse that takes pragmatic links between utterances seriously and incorporates them in the semantics. Next, it also aspires to cognitive reality and although the cognitive reality of the particular rules can be disputed, the view of discourse processing that they jointly produce is highly plausible.
However, a direct comparison with Gricean accounts of defaults is precluded by the fact that we would not be comparing like with like. In SDRT, the default interpretations are the defaults that are formalized with respect to the actually occurring discourse: there are rules that tell us how to take two events represented in two consecutive sentences, there are also rules that specify the relation between them depending on some features of their content.
For example, we cannot formalize the interpretation of 9a as 9b by means of rhetorical structure rules. The interpretation of 9a as 9b fits under the SDRT component ii rather than iii above, i. Merits of putting conventions into grammar are, however, not easy to find for a review see Jaszczolt b.
The computational semantics landscape contains a few landmarks in which the concept of a default figures prominently, albeit under different labels. I have already discussed the role of defaults and inheritance reasoning in artificial intelligence research in the example of SDRT. This kind of research in computational linguistics is arguably the closest to theoretical linguistic semantics and pragmatics in that it directly appeals to human practices in reasoning.
Pelletier and Elio write:. Other landmarks include research on default feature specification in syntactic theory and default lexical inheritance e. Gazdar et al. As a result, only the non-default features have to be attended to on various semantic networks in computational linguistics see also Stone To generalize, this line of research can lead to incorporation of information into logical forms, including, as can be seen in the example of SDRT, dynamic logical forms of discourses.
In a different camp there are statistical, distributional approaches to meaning where meaning is derived from information about co-occurrence of items gleaned from corpora and then quantitatively analysed. This orientation gave rise to current vector-based approaches see, e. Vector semantics exploits the finding that dates back at least to Harris and Firth that the meaning of a word can be computed from the distribution of the words in its immediate context.
Vectors can measure the similarity of texts with respect to a lexical item, the similarity of lexical items with respect to sources, or, what interests us most, the co-occurrence of selected words in a selection of contexts using additional methods to rule out co-occurrence by chance.
In distributional semantics therefore the salient or default meaning is the meaning given by the observed high co-occurrence or, in other words, delimited by the high conditional probability of its occurrence in the context of other words. Current compositional semantics is beginning to combine compositional semantic theory logic-based approaches discussed above with statistical models, conforming to the standard view of compositionality on which complex meanings are a function of lexical meanings and the mode of combination, arrived at through a recursive process, but at the same time aiming at capturing the generalization from finite past experiences that would inform machine learning.
Defaults arise in this context in several different forms: i as shortcuts to standard meanings of more semantically predictable categories, that is, closed-class words such as determiners, pronouns or sentential connectives. This can be extended perhaps to types of predictable projective content such as various types of implicature or presupposition; see Tonhauser et al.
Optimality-Theory pragmatics OT pragmatics, Blutner ; Blutner and Zeevat ; is another attempt at a computational modelling of discourse but unlike SDRT it makes use of a post-Gricean, intention-based account of discourse interpretation.
The process of interpretation is captured in a set of pragmatic constraints. The pragmatic additions to the underdetermined output of syntax are governed by a rationality principle called an optimization procedure that is spelled out as a series of constraints. These constraints are ranked as to their strength and they are defeasible, that is, they can be violated see Zeevat , The resulting interpretation of an utterance is the outcome of the working of such constraints.
OT pragmatics formalizes and extends the Gricean principles of cooperative communicative behaviour as found in Horn and Levinson , At the same time, this model can be regarded as producing default, presumed interpretations. With respect to finding an antecedent for an anaphor, for example, the interaction of the constraints explains the general tendency to look for the referent in the immediately preceding discourse rather than in the more remote fragments or, rather than constructing a referent ad hoc.
In other words, it explains the preference for binding over accommodation van der Sandt , Defaults in OT pragmatics combine the precision of a formal account with the psychological reality of Gricean intention-based explanations. Constraints are ranked, so to speak, post hoc : they explain what actually happened and why, rather than what should happen according to the rules of rational communicative behaviour.
In other words, context is incorporated even sooner into the process of utterance interpretation than in Gricean accounts and allows for non-defeasible, albeit standard, default, interpretations. With respect to this feature they resemble defaults of Default Semantics discussed in Section 1. In truth-conditional pragmatics Recanati, e. Pragmatic processing, however, is not necessarily fulfilled by conscious inference: processes that enrich the output of syntax are sub-doxastic, direct, and automatic.
The resulting representation of utterance meaning is the only representation that has cognitive reality and it is subject to truth-conditional analysis. On this account, the content of an utterance is arrived at directly, similar to the act of perception of an object.
Such processes enriching the actually uttered content are called primary pragmatic processes. Some of them make use of contextual information, others are context-independent. When the pragmatic addition constitutes a separate thought, it is, on this account, an implicature proper, arrived at through a secondary, conscious, and reflective pragmatic process. The latter process is called free enrichment.
Default interpretations are here defaults for processing of an utterance in a particular context. Recanati To sum up, such defaults ensue automatically, directly, without the effort of inference. One of the main questions to ask about any theory of utterance interpretation is what sources information about meaning comes from.
In Default Semantics, on the revised version of the theory Jaszczolt, e. WS is the output of the syntactic processing of the sentence, or its logical form. SD stands for the broadly understood context in which the discourse is immersed. IS pertains to properties of mental states which trigger certain types of interpretations. For example, the property of intentionality ensures that we normally use referring expressions with a referential intention that is the strongest for the given context.
SC pertains to the background knowledge of societal norms and customs and cultural heritage. WK encompasses information about physical laws, nature, environment, etc. It is important to stress that the four sources that accompany WS do not merely enrich the output of the latter. This constitutes a substantial breakaway from the established boundary between explicit and implicit content.
The identification of the sources also allows us to propose a processing model in Default Semantics in which three types of contribution to utterance interpretation are distinguished: i processing of the sentence called combination of word meaning and sentence structure, WS ; ii conscious pragmatic inference CPI from three of the sources distinguished above: SD, SC, and WK; and iii two kinds of default, automatic meanings: cognitive defaults CD triggered by the source IS, and social, cultural and world-knowledge defaults SCWD.
The primary meaning is arrived at through the interaction of these processes and therefore need not bear close resemblance to the logical form of the sentence; the output of WS can vary in significance as compared with the output of other types of processes. There may also be other communicated meanings but those fall in the domain of implicatures.
In Default Semantics, the primary content of an utterance is its most salient meaning. This is so even when this meaning does not bear any resemblance to the logical form derived from the syntactic structure of the uttered sentence.
In other words, CPI can override WS and produce, say, 12c as utterance meaning called primary meaning , represented in a merger representation for the given context. Some of them arise due to the properties of words or constructions used and are present by default independently of the context of the utterance, while others are default meanings for the particular situation of discourse.
CDs are default interpretations that are triggered by the properties of mental states. For example, when speakers use a definite description in an utterance, they normally use it referentially about a particular, known, intersubjectively recognisable individual rather than attributively about whoever fits the description.
This default referential use can be given a functional as well as a cognitive explanation. Firstly, it can be explained in terms of the strength of the referential intention associated with the act of utterance: ceteris paribus, humans provide the strongest information relevant and available to them. Like the strongest referring, so the strongest aboutness, is the norm, the default. Next, SCWDs are default interpretations that arise due to the shared cultural and social background of the interlocutors.
To use a well worn example, in 14a , it is the shared presumption that babies are raised by their own mothers that allows the addressee to arrive at 14b. The natural concomitant of reducing the role of the logical form WS to one of four equally potent constituents of utterance meaning is a revised view of compositionality. Install the exe Download the NodeJS executable.
Install Gulp Semantic UI uses Gulp to provide command line tools for building themed versions of the library with just the components you need. Gulp is an NPM module and must be installed globally npm install -g gulp. All Set! Well done! Semantic UI is now ready to be used. See how to use gulp commands and build tools. Learn about changing themes. See recipes for using Semantic UI in your project. Donate Today. The Translation Needs Your Help. For microcontroller programming, there are three commonly used commands: make , make flash and make clean.
I made three interactive functions for these three commands and map them to three keybindings by the following:. The reason why all three commands have cd..
Two interactive functions are made to switch from one to another by the following:. Emacs Development Environment. RTags Github Repo.
In Emacs, load RTags with the following code after installation: rtags-enable-standard-keybindings setq rtags-autostart-diagnostics t rtags-diagnostics. Syntax Checking and Formatting RTags can be integrated with Flycheck by flycheck-rtags package using the following function: require 'flycheck-rtags defun flycheck-rtags-setup "Configure flycheck-rtags. Commands for Embedded Systems For microcontroller programming, there are three commonly used commands: make , make flash and make clean.
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