Lemmatization, PoS and Parsing Request [2.0]

Request

Requests are made using GET or POST data submissions to the API entry point. Typically, a POST method is recommended in order to overcome the parameter maximum length limit associated to the GET method.

Request

Endpoint

This is the endpoint to access the API.

Service	Method	Url
Lemmatization, PoS and Parsing	POST	https://api.meaningcloud.com/parser-2.0	Console

If you are working with an on-premises installation, you will need to substitute api.meaningcloud.com by your own server address.

Parameters

These are the supported parameters.

Name	Description	Values	Default
`key`	The access key is required for making requests to any of our web services. You can get a valid access key for free just by creating an account at MeaningCloud.		Required
`of`	Output format.	xml json img	Optional. Default: `of=json`
`lang`	It specifies the language in which the text must be analyzed.	en: English es: Spanish it: Italian fr: French pt: Portuguese ca: Catalan	Required
`ilang`	It specifies the language in which the values returned will appear (in the case where they are known). Check the response section to see which fields are affected.	en: English es: Spanish it: Italian fr: French pt: Portuguese ca: Catalan	Optional. Default: same as `lang`
`verbose`	Verbose mode. When active, it shows additional information about the morphosyntactic tagsets and sentiment analysis. It provides an in depth description of the tagsets and shows the changes applied to the basic polarity of the different polarity terms detected.	y: enabled n: disabled	Optional. Default: `verbose=n`
`txt`	Input text that's going to be analyzed.	UTF-8 encoded text (plain text, HTML or XML).	Optional. Default: `txt=""`
`txtf`	The text format parameter specifies if the text included in the txt parameter uses markup language that needs to be interpreted (known HTML tags and HTML code will be interpreted, and unknown tags will be ignored).	plain markup	Optional. Default: `txtf=plain`
`url`	URL with the content to analyze. Currently only non-authenticated HTTP and FTP are supported. The content types supported for URL contents can be found here.		Optional. Default: `url=""`
`doc`	Input file with the content to analyze. The supported formats for file contents can be found here.		Optional. Default: `doc=""`
`uw`	Deal with unknown words. This feature adds a stage to the topic extraction in which the engine, much like a spellchecker, tries to find a suitable analysis to the unknown words resulted from the initial analysis assignment. It is specially useful to decrease the impact typos have in text analyses.	y: enabled n: disabled	Optional. Default: `uw=n`
`rt`	Deal with relaxed typography. This parameter indicates how reliable the text (as far as spelling, typography, etc. are concerned) to analyze is, and influences how strict the engine will be when it comes to take these factors into account in the topic extraction.	y: enabled u: enabled only for user dictionary n: disabled	Optional. Default: `rt=n`
`dm`	Type of disambiguation applied. It is accumulative, that is, the semantic disambiguation mode will also include morphosyntactic disambiguation.	n: no disambiguation m: morphosyntactic disambiguation s: semantic disambiguation	Optional. Default: `dm=s`
`sdg`	Semantic disambiguation grouping. This parameter will only apply when semantic disambiguation is activated (`dm=s`). See disambiguation grouping for a more in depth explanation.	n: none g: global intersection t: intersection by type l: intersection by type - smallest location	Optional. Default: `sdg=l`
`cont`	Disambiguation context. Context prioritization for entity semantic disambiguation. See context disambiguation for a more in depth explanation.		Optional. Default: `cont=""`
`ud`	The user dictionary allows to include user-defined entities and concepts in the analysis. It provides a mechanism to adapt the process to focus on specific domains or on terms relevant to a user's interests, either to increase the precision in any of the domains already taken into account in our ontology to include a new one, or just to add a new semantic meaning to known terms. Several dictionaries can be combined separating them with `\|`.	Name of your user dictionaries.	Optional. Default: `ud=""`
`tt`	The list of topic types to extract will be specified through a string with the letters assigned to each one of the topic types that are to be extracted.	e: named entities c: concepts t: time expressions m: money expressions n: quantity expressions [beta] o: other expressions q: quotations r: relations a: all	Optional. Default: `tt=""`
`st`	Show subtopics. This parameter will indicate if subtopics are to be shown. See subtopics for a more in depth explanation.	y: enabled n: disabled	Optional. Default: `st=n`
`timeref`	This value allows to set a specific time reference to detect the actual value of all the relative time expressions detected in the text. It only applies when time expressions are enabled in `tt`.	YYYY-MM-DD hh:mm:ss GMT±HH:MM	Optional. Default: current time at the moment the request is made.
`sm`	Sentiment model chosen. If sent empty, sentiment analysis info will not be included in the response.	`general`: general model. Automatic language detection.	Optional. Default: `sm=""`
`egp`	Expand global polarity. This mode allows you to choose between two different algorithms for the polarity detection of entities and concepts. Enabling the parameter gives less weight to the syntactic relationships, so it's recommended for short texts with unreliable typography. It only applies when `sm!=""`.	y: enabled n: disabled	Optional. Default: `egp=n`

Important

The fields txt, doc and url are mutually exclusive; in other words, at least one of them must not be empty (a content parameter is required), and in cases where more than one of them has a value assigned, only one will be processed. The precedence order is txt, url and doc.