We have released a new version of our core linguistic analyzer: Lemmatization, PoS and Parsing. In Lemmatization, PoS and Parsing 2.0:
- More analysis possibilities have been included to allow you to combine a complete morphosyntactic analysis with other types of analysis such as Sentiment Analysis and Topics Extraction.
- Configuration options have been changed to provide more flexibility in the analyses and to make the options available more understandable.
- We’ve refactored our code to:
- Improve the quality of the concepts/keywords extraction.
- Make easier and more flexible the use and traceability of user dictionaries.
- Give the possibility of obtaining a more complex integrated analysis to give flexibility in complex scenarios where the standard output is not enough.
- A new type of topic has been added, quantity expressions, to cover a specific type of information that was hard to obtain with previous versions.
- Some fields in the output have been modified, either to give them more appropriate names or to make them easier to use and understand.
- Some use modes have been retired as the information provided was redundant with what a morphosyntactic analysis already gives.
All these improvements mean the migration process is not as fast as it would be with a minor version. These are the things you need to know to migrate your applications from Lemmatization, PoS and Parsing 1.2 to Lemmatization, PoS and Parsing 2.0.
Request
The most relevant changes in the request are the following:
| Lemmatization, PoS and Parsing 1.2 | Lemmatization, PoS and Parsing 2.0 | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Endpoint | http://api.meaningcloud.com/parser-1.2 | http://api.meaningcloud.com/parser-2.0 | ||||||||||||
Parameter ilang |
Did not exist. | It has the same values available as lang. |
||||||||||||
Parameter mode |
Accepted values:
|
Disappears and behaves as it did with mode=sa. Modes ma and l can be obtained from the morphosyntactical analysis. |
||||||||||||
Parameter dm |
|
It has been divided into two parameters: dm and sdg with the following equivalences:
|
||||||||||||
Parameter tt |
Accepted values:
|
Accepted values:
|
||||||||||||
Parameter cs |
y or n | Disappears and behaves as it did with the default value. | ||||||||||||
Parameter dic |
Use of thematic dictionaries, by default they were all loaded. | Disappears and behaves as it did with the default value. | ||||||||||||
Parameter sm |
It did not exist. | Model name value for the selected lang to use in the Sentiment Analysis. Currently:
|
||||||||||||
Parameter egp |
It did not exist. | Changes the algorithm used for the sentiment analysis. | ||||||||||||
Parameter verbose |
Did not exist. | Shows some additional fields. |
All the other parameters from Lemmatization, PoS and Parsing 1.2 not explicitly mentioned behave exactly the same in Lemmatization, PoS and Parsing 2.0.
For those of you who are using the modes that have been retired in the new version (mode=ma and mode=l), we’ve included examples of how to use the output to get those same results: morphological analysis and lemmatization.
Response
The complete response is documented in detail in the documentation, so here we’ll just comment on the most important points:
- All the fields associated to style aspects of the text analyzed are now grouped under a
styleelement. - There’s a new field,
affected_by_negation, that indicates if a token is considered to be affected by a negator. - The topics extracted in
topics_listhave changed. Some are new (quantity_expression), some have been moved around (phone expressions,uri_expressions), and some have been restructured (quotations,money_expressions). You can read all the details in the Topics Extraction 2.0 migration guide. - Sentiment analysis now can be added to the morphosyntactic analysis. This will be done in two ways: through a
global_sentimentelement that gives sentiment information for the whole text analyzed and throughsentiment, which will appear in thetokenobject, and will indicate if the token has a polarity associated or if it inherits polarity from another token. - Semantic senses now have more information associated to them (
formandofficial_form) and are dependent on theilangdefined. - The morphosyntactic analysis of each token no longer contains information about the thematic dictionary it belongs to, only standardized information of the variety dictionary (in the cases it applies).
In the following table, you can see side by side how the analysis of the sentence “He said he wanted 50% of the $6 million from the robbery that occurred in London” changes between versions.
|
Lemmatization, PoS and Parsing 1.2
Lemmatization, PoS and Parsing 2.0
|
|---|
{
"status": {
"code": "0",
"msg": "OK",
"credits": "1"
},
"token_list": [
{
"type": "sentence",
"id": "38",
"inip": "0",
"endp": "79",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "A",
"quote_level": "0",
"title": "no",
"token_list": [
{
"form": "He",
"id": "1",
"inip": "0",
"endp": "1",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "_",
"quote_level": "0",
"title": "no",
"analysis_list": [
{
"tag": "PPMS3NN8",
"lemma": "he",
"original_form": "he",
"sense_id_list": [
{
"sense_id": "PRONHUMAN"
}
]
}
],
"sense_list": [
{
"id": "PRONHUMAN",
"info": "semhum=human"
}
]
},
{
"form": "said",
"id": "2",
"inip": "3",
"endp": "6",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "0",
"title": "no",
"analysis_list": [
{
"tag": "VI-S3ASA-N-N8",
"lemma": "say",
"original_form": "said",
"sense_id_list": [
{
"sense_id": "ODENTITY_COMMUNICATION_PROCESS"
},
{
"sense_id": "ODENTITY_LINGUISTIC_COMMUNICATION"
},
{
"sense_id": "ODENTITY_PROCESS"
}
]
}
],
"sense_list": [
{
"id": "ODENTITY_COMMUNICATION_PROCESS",
"info": [...]
},
{
"id": "ODENTITY_LINGUISTIC_COMMUNICATION",
"info": [...]
},
{
"id": "ODENTITY_PROCESS",
"info": [...]
}
]
},
{
"form": "he",
"id": "3",
"inip": "8",
"endp": "9",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "PPMS3NN8",
"lemma": "he",
"original_form": "he",
"sense_id_list": [
{
"sense_id": "PRONHUMAN"
}
]
}
],
"sense_list": [
{
"id": "PRONHUMAN",
"info": "semhum=human"
}
]
},
{
"form": "wanted",
"id": "4",
"inip": "11",
"endp": "16",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "VI-S3ASA-N-N2",
"lemma": "want",
"original_form": "wanted",
"sense_id_list": [
{
"sense_id": "ODENTITY_INTENTIONAL_PSYCHOLOGICAL_PROCESS"
},
{
"sense_id": "ODENTITY_LINGUISTIC_COMMUNICATION"
}
]
}
],
"sense_list": [
{
"id": "ODENTITY_INTENTIONAL_PSYCHOLOGICAL_PROCESS",
"info": [...]
},
{
"id": "ODENTITY_LINGUISTIC_COMMUNICATION",
"info": [...]
}
]
},
{
"type": "multiword",
"form": "50%",
"id": "20",
"inip": "18",
"endp": "20",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"head": "6",
"title": "no",
"analysis_list": [
{
"tag": "NCMS-n-",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "NCMP-n-",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "NCFS-n-",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "NCFP-n-",
"lemma": "50%",
"original_form": "50%"
}
]
},
{
"form": "of",
"id": "7",
"inip": "22",
"endp": "23",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "YN9",
"lemma": "of",
"original_form": "of"
}
]
},
{
"form": "the",
"id": "8",
"inip": "25",
"endp": "27",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "TD-PN9",
"lemma": "the",
"original_form": "the"
}
]
},
{
"form": "$",
"id": "9",
"inip": "29",
"endp": "29",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "NCMP-s-",
"lemma": "$",
"original_form": "$",
"sense_id_list": [
{
"sense_id": "^_9145003407816029121"
}
]
},
{
"tag": "NCFP-s-",
"lemma": "$",
"original_form": "$",
"sense_id_list": [
{
"sense_id": "^_9145003407816029121"
}
]
}
],
"sense_list": [
{
"id": "^_9145003407816029121",
"info": "sementity/class=class@type=Top>Unit>Currency"
}
]
},
{
"form": "6 million",
"normalized_form": "numeric@6e+06",
"id": "21",
"inip": "30",
"endp": "38",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "A",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "MDMPCn-",
"lemma": "6 million",
"original_form": "6 million"
},
{
"tag": "MDFPCn-",
"lemma": "6 million",
"original_form": "6 million"
}
]
},
{
"form": "from",
"id": "12",
"inip": "40",
"endp": "43",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "YN8",
"lemma": "from",
"original_form": "from"
}
]
},
{
"form": "the",
"id": "13",
"inip": "45",
"endp": "47",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "TD-SN9",
"lemma": "the",
"original_form": "the"
}
]
},
{
"form": "robbery",
"id": "14",
"inip": "49",
"endp": "55",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "NC-S-N3",
"lemma": "robbery",
"original_form": "robbery",
"sense_id_list": [
{
"sense_id": "c3784c490b"
}
]
}
],
"sense_list": [
{
"id": "c3784c490b",
"info": [...]
}
]
},
{
"form": "that",
"id": "15",
"inip": "57",
"endp": "60",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "RP-SN5",
"lemma": "that",
"original_form": "that"
},
{
"tag": "RP-PN5",
"lemma": "that",
"original_form": "that"
}
]
},
{
"form": "occurred",
"id": "16",
"inip": "62",
"endp": "69",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "VI-S3ASA-N-N6",
"lemma": "occur",
"original_form": "occurred",
"sense_id_list": [
{
"sense_id": "ODENTITY_INTENTIONAL_PSYCHOLOGICAL_PROCESS"
},
{
"sense_id": "ODENTITY_PROCESS"
}
]
},
{
"tag": "VI-P3ASA-N-N6",
"lemma": "occur",
"original_form": "occurred",
"sense_id_list": [
{
"sense_id": "ODENTITY_INTENTIONAL_PSYCHOLOGICAL_PROCESS"
},
{
"sense_id": "ODENTITY_PROCESS"
}
]
}
],
"sense_list": [
{
"id": "ODENTITY_INTENTIONAL_PSYCHOLOGICAL_PROCESS",
"info": [...]
},
{
"id": "ODENTITY_PROCESS",
"info": [...]
}
]
},
{
"form": "in",
"id": "17",
"inip": "71",
"endp": "72",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "YN6",
"lemma": "in",
"original_form": "in"
}
]
},
{
"form": "London",
"id": "18",
"inip": "74",
"endp": "79",
"bold": "no",
"italic": "no",
"underscore": "no",
"separation": "1",
"quote_level": "1",
"title": "no",
"analysis_list": [
{
"tag": "NP-S-N-",
"lemma": "London",
"original_form": "London",
"sense_id_list": [
{
"sense_id": "01d0d69c7d"
}
]
}
],
"sense_list": [
{
"id": "01d0d69c7d",
"info": [...]
}
]
}
]
}
]
}
{
"status": {
"code": "0",
"msg": "OK",
"credits": "1"
},
"token_list": [
{
"type": "sentence",
"id": "23",
"inip": "0",
"endp": "79",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "A",
"quote_level": "0",
"affected_by_negation": "no",
"token_list": [
{
"type": "phrase",
"form": "He said he wanted 50% of the $6 million from the robbery that occurred in London",
"id": "37",
"inip": "0",
"endp": "79",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "_",
"quote_level": "0",
"affected_by_negation": "no",
"analysis_list": [
{
"tag": "Z-----------",
"lemma": "*",
"original_form": "He said he wanted 50% of the $6 million from the robbery that occurred in London"
}
],
"token_list": [
{
"type": "phrase",
"form": "He",
"id": "31",
"inip": "0",
"endp": "1",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "_",
"quote_level": "0",
"affected_by_negation": "no",
"head": "1",
"syntactic_tree_relation_list": [
{
"id": "2",
"type": "isSubject"
}
],
"analysis_list": [
{
"tag": "GNMS3S--",
"lemma": "he",
"original_form": "He"
}
],
"token_list": [
{
"form": "He",
"id": "1",
"inip": "0",
"endp": "1",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "_",
"quote_level": "0",
"affected_by_negation": "no",
"analysis_list": [
{
"tag": "PPMS3NN8",
"lemma": "he",
"original_form": "he",
"sense_id_list": [
{
"sense_id": "PRONHUMAN"
}
]
}
],
"sense_list": [
{
"id": "PRONHUMAN",
"form": "he",
"info": "semhum=human"
}
]
}
]
},
{
"form": "said",
"id": "2",
"inip": "3",
"endp": "6",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "1",
"quote_level": "0",
"affected_by_negation": "no",
"syntactic_tree_relation_list": [
{
"id": "31",
"type": "iof_isSubject"
},
{
"id": "36",
"type": "iof_isDirectObject"
}
],
"analysis_list": [
{
"tag": "VI-S3ASA-N-N8",
"lemma": "say",
"original_form": "said",
"sense_id_list": [
{
"sense_id": "ODENTITY_COMMUNICATION_PROCESS"
},
{
"sense_id": "ODENTITY_LINGUISTIC_COMMUNICATION"
},
{
"sense_id": "ODENTITY_PROCESS"
}
]
}
],
"sense_list": [
{
"id": "ODENTITY_COMMUNICATION_PROCESS",
"form": "say",
"info": [...]
},
{
"id": "ODENTITY_LINGUISTIC_COMMUNICATION",
"form": "say",
"info": [...]
},
{
"id": "ODENTITY_PROCESS",
"form": "say",
"info": "sementity/id=ODENTITY_PROCESS@type=Top>Process\tsemld_list=sumo:Entity"
}
]
},
{
"type": "phrase",
"form": "he wanted 50% of the $6 million from the robbery that occurred in London",
"id": "36",
"inip": "8",
"endp": "79",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "1",
"quote_level": "1",
"affected_by_negation": "no",
"syntactic_tree_relation_list": [
{
"id": "2",
"type": "isDirectObject"
}
],
"analysis_list": [
{
"tag": "ZN---D------",
"lemma": "*",
"original_form": "he wanted 50% of the $6 million from the robbery that occurred in London"
}
],
"token_list": [
{
"type": "phrase",
"form": "he",
"id": "30",
"inip": "8",
"endp": "9",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "1",
"quote_level": "1",
"affected_by_negation": "no",
"head": "3",
"syntactic_tree_relation_list": [
{
"id": "4",
"type": "isSubject"
}
],
"analysis_list": [
{
"tag": "GNMS3S--",
"lemma": "he",
"original_form": "he"
}
],
"token_list": [
{
"form": "he",
"id": "3",
"inip": "8",
"endp": "9",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "1",
"quote_level": "1",
"affected_by_negation": "no",
"analysis_list": [
{
"tag": "PPMS3NN8",
"lemma": "he",
"original_form": "he",
"sense_id_list": [
{
"sense_id": "PRONHUMAN"
}
]
}
],
"sense_list": [
{
"id": "PRONHUMAN",
"form": "he",
"info": "semhum=human"
}
]
}
]
},
{
"form": "wanted",
"id": "4",
"inip": "11",
"endp": "16",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "1",
"quote_level": "1",
"affected_by_negation": "no",
"syntactic_tree_relation_list": [
{
"id": "30",
"type": "iof_isSubject"
},
{
"id": "25",
"type": "iof_isDirectObject"
}
],
"analysis_list": [
{
"tag": "VI-S3ASA-N-N2",
"lemma": "want",
"original_form": "wanted",
"sense_id_list": [
{
"sense_id": "ODENTITY_INTENTIONAL_PSYCHOLOGICAL_PROCESS"
},
{
"sense_id": "ODENTITY_LINGUISTIC_COMMUNICATION"
}
]
}
],
"sense_list": [
{
"id": "ODENTITY_INTENTIONAL_PSYCHOLOGICAL_PROCESS",
"form": "want",
"info": [...]
},
{
"id": "ODENTITY_LINGUISTIC_COMMUNICATION",
"form": "want",
"info": [...]
}
]
},
{
"type": "phrase",
"form": "50% of the $6 million from the robbery that occurred in London",
"id": "25",
"inip": "18",
"endp": "79",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "1",
"quote_level": "1",
"affected_by_negation": "no",
"head": "20",
"syntactic_tree_relation_list": [
{
"id": "4",
"type": "isDirectObject"
},
{
"id": "29",
"type": "iof_isAnaphora"
}
],
"analysis_list": [
{
"tag": "GNMS3D--",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "GNMP3D--",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "GNFS3D--",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "GNFP3D--",
"lemma": "50%",
"original_form": "50%"
}
],
"token_list": [
{
"type": "multiword",
"form": "50%",
"normalized_form": "numeric@0.5",
"id": "20",
"inip": "18",
"endp": "20",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "1",
"quote_level": "1",
"affected_by_negation": "no",
"head": "6",
"analysis_list": [
{
"tag": "NCMS-n-",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "NCMP-n-",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "NCFS-n-",
"lemma": "50%",
"original_form": "50%"
},
{
"tag": "NCFP-n-",
"lemma": "50%",
"original_form": "50%"
}
]
},
{
"type": "phrase",
"form": "of the $6 million from the robbery",
"id": "34",
"inip": "22",
"endp": "55",
"style": {
"isBold": "no",
"isItalics": "no",
"isUnderlined": "no",
"isTitle": "no"
},
"separation": "1",
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}
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}
]
}
|
Again, all the details can be found in the Lemmatization, PoS and Parsing 2.0 documentation. Remember! Lemmatization, PoS and Parsing 1.2 will be retired on February 29, so make sure to adapt your integration by then. If you have any questions or issues during the migration, we are always available either through our support form, or just by writing us to support@meaningcloud.com.
