Response
Sample response:
The restaurant was great even though it’s not near Madrid.
{
"status":{
"code":
"0"
"msg":
"OK"
"credits":
"1"
"model":
"general_en"
"score_tag":
"P+"
"agreement":
"AGREEMENT"
"subjectivity":
"OBJECTIVE"
"confidence":
"100"
"irony":
"NONIRONIC"
"sentence_list":[
0:{
"text":
"The restaurant was great even though it’s not near Madrid."
"inip":
"0"
"endp":
"57"
"bop":
"y"
"confidence":
"100"
"score_tag":
"P+"
"agreement":
"AGREEMENT"
"segment_list":[
...
]"sentimented_entity_list":[
...
]"sentimented_concept_list":[
...
]"sentimented_entity_list":[
0:{
"form":
"Madrid"
"id":
"3d0a16c68d"
"type":
"Top>Location>GeoPoliticalEntity>City"
"score_tag":
"NONE"
"sentimented_concept_list":[
0:{
"form":
"restaurant"
"id":
"4d5e117421"
"type":
"Top>Location>Facility"
"score_tag":
"P+"
Response object:
| Name | Description |
|---|---|
status | Describes the request outcome in terms of success or failure. |
status.code | Numerical value of result code. Refer to the error code catalog. |
status.msg | Human-readable error code, if any, orOK. |
status.credits | Credits consumed by the request. A credit corresponds to a bucket of 500 words. Did you know...?Only successful requests consume credits. |
status.remaining_credits | Credits left to reach the usage limit. |
model | Holds the model used in the evaluation followed by an underscore and the language in which the analysis has been carried out. |
score_tag | Polarity of the element it refers to: global polarity,polarity_term, sentimented_concept, sentimented_entity, segment or sentence. Possible values:
|
agreement | Marks the agreement between the sentiments detected in the text, the sentence or the segment it refers to. It has two possible values:
|
subjectivity | Marks the subjectivity of the text. It has two possible values:
|
confidence | represents the confidence associated with the sentiment analysis performed on the text. Its value is an integer number in the 0-100 range. |
irony | Indicates the irony of the text. It has two possible values:
|
sentence_list | List of sentences in which the text is divided. Each sentence is represented by a sentence object. |
sentimented_entity_list | This is a list of the entities identified in the text with a certain polarity. These entities are the same ones that would be detected by the Topics Extraction API, the only difference will be in the Hashtags, Cashtags and Nicknames entities. These cases, because of their special importance in social media analyses, will also include (in the cases they have it), their known subtopics. For instance, if @BBC is detected, it will apear as a nickname, but also as the entity "BBC" (a Media Company). Each one will be represented by an element sentimented entity. |
sentimented_concept_list | This is a list of the concepts identified in the text with a certain polarity. Each one will be represented by an element sentimented concept. |
Sentence object
A sentence in the text is represented by a sentence objects with the following structure:
Sentence object attributes
| Name | Description |
|---|---|
text | Text of the sentence |
inip | Position of the first character of the sentence (zero indexed). |
endp | Position of the last character of the sentence (zero indexed). |
bop | Marks if the sentence is the beginning if the paragraph (y or n) |
confidence | Refer to the confidence parameter in the response object. |
score_tag | Refer to the score_tag parameter in the response object. |
agreement | Refer to the agreement parameter in the response object. |
segment_list | List of segments in which each sentence has been divided to perform the analysis. Each segment represents a fragment of the sentence that expresses a single opinion |
segment_list[].text | Text of the segment |
segment_list[].segment_type | This field indicates if the segment has been used to compute the aggregated polarity of its parent. It has two possible values:
|
segment_list[].inip | Position of the first character of the segment (zero indexed). |
segment_list[].endp | Position of the last character of the segment (zero indexed). |
segment_list[].confidence | Refer to the confidence parameter in the response object. |
segment_list[].score_tag | Refer to the score_tag parameter in the response object. |
segment_list[].agreement | Refer to the agreement parameter in the response object. |
segment_list[].polarity_term_list | List of words with polarity found in the segment. Polarity terms may have different polarities depending on their context: their polarity may be amplified, inverted or determined by their surrounding words. |
segment_list[].polarity_term_list[].text | Text of the term, including in parentheses the polarity modifiers it is affected by, and the context words used to determine its polarity. In the cases where the polarity term is formed by several words, they will be separated by _. |
segment_list[].polarity_term_list[].inip | Position of the first character of the term (zero indexed). |
segment_list[].polarity_term_list[].endp | Position of the last character of the term (zero indexed). |
segment_list[].polarity_term_list[].tag_stack | Polarity modifiers affecting this polarity term. It appears only when verbose=y. |
segment_list[].polarity_term_list[].confidence | Refer to the confidence parameter in the response object. |
segment_list[].polarity_term_list[].score_tag | Refer to the score_tag parameter in the response object. |
segment_list[].polarity_term_list[].sentimented_entity_list | In the cases where they exist, this will contain a list of entities affected by the polarity term. Each element will be tagged as a sentimented entity object. |
segment_list[].polarity_term_list[].sentimented_concept_list | In the cases where they exist, this will contain a list of concepts affected by the polarity term. Each element will be tagged as a sentimented entity object. |
segment_list[].segment_list | Each segment can have another segment_list field if the sentiment analyzer detects smaller segments inside it. These segments are the smallest level of fragmentation that the system can detect. This second level of elements will only appear if necessary. |
segment_list[].sentimented_entity_list | List of the entities identified in the segment but that are not affected by the polarity terms identified in it. |
segment_list[].sentimented_concept_list | List of the concepts identified in the segment but that are not affected by the polarity terms identified in it. |
sentimented_entity_list | List of the entities identified in the sentence. |
sentimented_concept_list | List of the concepts identified in the sentence. |
Entity and concept objects
The entities and concepts that are detected in the text will appear in different elements of the output. The sentimented_entity_list and sentimented_concept_list associated to polarity terms will contain the same polarity information as the polarity term they are included in; they will also have information about the entity/concept appearance. In the case of the entities not affected by the polarity of a segment, they will also contain information about their appearance and the polarity value associated will be NONE.
Both elements have the same fields:
Sentence object attributes
| Name | Description |
|---|---|
form | Main form of the entity/concept in the language specified in the ilang parameter. |
id | ID of the entity/concept. This ID will correspond to its senseID in resources (including user resources). If the entity/concept has been detected in the analysis, the ID will be specifically created for that analysis and will begin by two underscores. |
variant | How the entity/concept appears in the text (only in polarity_term elements). |
inip | Position of the first character of the entity or concept (only in polarity_term elements, zero indexed). |
endp | Position of the last character of the entity or concept (only in polarity_term elements, zero indexed). |
type | Ontology type of the entity/concept. Refer to MeaningCloud's ontology. |
score_tag | Refer to the score_tag parameter in the response object. |
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