MPAI-MMC V2.2 Datasets

<-Data Types Go to ToC

1 Introduction	2 Text with Emotion	3 Audio and Video Files with Emotion	4 Emotion JSON Files
5 Meaning JSON Files	6 Question Text Files	7 Question Speech Files	8 Images for Questions
9 Meaning JSON Files for Questions	10 Intention JSON Files

1 Introduction

Testing the Conformance of MMC-CWE, MMC-MQA, and MMC-UST requires datasets to test Data, AIMs, and AIWs. The Data Formats belong to one of Text, Audio, Video, and JSON and should have the characteristics of Table 1:

Table 1 – Data Types for Conformance Testing of MMC-CWE, MMC-MQA, and MMC-UST

Data Type	Characteristics
Text	The texts files shall be composed of Unicode characters.
Speech file	The speech files shall be conforming .wav files.
Video file	The video files shall be conforming MP4 files.
Image File	The Image file shall be conforming
Emotion	Emotion files shall be JSON files conforming with the Emotion JSON Schema.
Intention	Emotion files shall be JSON files conforming with the Intention JSON Schema.
Meaning	Emotion files shall be JSON files conforming with the Meaning JSON Schema.

Humans shall carry out Conformance Testing by visual and auditory inspection. Appropriate software may replace humans as Conformance Testers.

Conformance Testing Datasets are publicly available upon registration.

2 Text with Emotion

2.1 Coherent scenarios

Happy	1. Today was a wonderful day. I spent quality time with my parents, and the restaurant was excellent as well. I look forward to seeing them again!
	2. I’m so excited about Christmas. This year, my girlfriend and I are going to celebrate the holiday together. We’ll decorate our room, and it’ll be so much fun.
	3. Today I watched a movie called ‘The Pianist.’ Not only was it touching, but also very absorbing. Now I feel very happy thanks to the memorable experience.
	4. The weather is awesome these days. It is not too cold, not too hot, and the sun shines beautifully. I look forward to the picnic that is scheduled this weekend.
	5. Nowadays my business is running very smoothly. There are no unexpected issues arising, and my employees are working very diligently. I am very relieved.
Angry	1. Today my coworkers treated me really badly. They blamed me for the things that were neither my responsibility nor the result of my actions. This is so unfair.
	2. I am angry with my sister. She not only does not finish her chores, but forces me to do the chores for her. This is not a new occasion, but this time I can’t,
	stand it.
	3. Yesterday I had an argument with a friend of mine. He always wants me to listen to him very carefully and provide advice, but when I’m in need of the help of the same sort, he doesn’t fulfill his duty at all. I’m furious about this.
	4. These days consumer price is skyrocketing. However, the government and political parties are busy blaming the external variables, not trying hard to solve.
	the problem that ordinary citizens are facing. Why is there no one trying to be responsible?
	5. Because of my superior in my workplace, I am doing monotonous tasks all day long these days. I have to look at thousands of boring images and classify them each day, which drives me crazy. I cannot but blame my superior.
Neutral	1. Seoul is the capital city of the Republic of Korea. It is a city of almost ten million residents. According to “The Global Livability Index” Seoul is ranked the fourth most livable city in Asia as of 2023.
	2. There is a famous proverb, “Honesty is the best policy.” In essence, it suggests that honesty is the most effective and beneficial approach in various aspects of life.
	3. There is a famous saying, “Don’t judge a book by its cover.” This advises people not to form an opinion or make assumptions about someone or something based solely on its outward appearance.
	4. Global warming refers to the long-term increase in Earth’s average surface temperature due to human activities, primarily the emission of greenhouse gases. Greenhouse gases trap heat in the Earth’s atmosphere, leading to the warming effect.
	5. Inflation is a general increase of the prices of goods and services in an economy. This is usually measured using the consumer price index (CPI).

2.2 Incoherent scenarios

Text	Meaning	Speech	Face	Sentences
Happy	Happy	Angry	Angry	I’m headed to a yoga class now, and then I have a cozy evening planned with a good book. Life is good, for sure.
Happy	Happy	Neutral	Neutral	With a big scoop of ice cream in hand, I laughed and played in the park, feeling super happy as the sun shone brightly overhead.
Angry	Angry	Happy	Happy	Witnessing my neighbor being rude and disrespectful to an old stranger asking for directions, I couldn’t be sane, because that old man was my father.
Neutral	Neutral	Happy	Happy	A political party is an organization that coordinates candidates to compete in a particular country’s elections. It is common for the members of a party to hold similar ideas about politics.
Neutral	Neutral	Angry	Angry	According to Max Weber, a state is a compulsory political organization with a centralized government that maintains a monopoly of the legitimate use of force within a certain territory.

3 Audio and Video with Emotion

4 Emotion JSON Files

The JSON files below represent Happy, Angry, and Neutral Emotions.

{

“EmotionType”:{

“emotionDegree”:”high”,

“emotionName”:”happy”,

“emotionSetName”:”MPAI Basic Emotion Set”

}

{

“EmotionType”:{

“emotionDegree”:”high”,

“emotionName”:”happy”,

“emotionSetName”:”MPAI Basic Emotion Set”

}

{

“EmotionType”:{

“emotionDegree”:”high”,

“emotionName”:”happy”,

“emotionSetName”:”MPAI Basic Emotion Set”

}

5 Meaning JSON Files

Sentence 1: Today was a wonderful day! I spent quality time with my parents, and the McDonald restaurant was excellent, too. I’m looking forward to seeing them again!

{

“meaning”: {

“POS_tagging”: {

“POS_tagging_set”: “CST’s Part-Of-Speech tagger (Brill, with adaptations)”,

“POS_tagging_result”: “Today/RB was/VBD a/DT wonderful/JJ day/NN !/. I/PRP spent/VBD quality/NN time/NN with/IN my/PRP$ parents/NNS ,/, and/CC the/DT McDonald/NNP restaurant/NN was/VBD excellent/JJ ,/, too/RB ./. I’m/NNP looking/VBG forward/RB to/TO seeing/VBG them/PRP again/RB !/.”

“NE_tagging”: {

“NE_tagging_set”: “CST’s named entity recogniser”,

“NE_tagging_result”: ” [Today,misc,uncertain] was a wonderful day ! I spent quality time with my parents, and the [McDonald,person,likely] restaurant was excellent , too . I’m looking forward to seeing them again!”

“dependency_tagging”: {

“dependency_tagging_set”: “CG-dependency, https://edu.visl.dk/visl/en/parsing/automatic/dependency.php “,

“dependency_tagging_result”: “<ß>nToday [today] <*> <atemp> ADV @ADVL> #1->2nwas [be] <mv> V IMPF 1/3S @FS-STA #2->0na [a] <indef> ART S @>N #3->5nwonderful [wonderful] ADJ POS @>N #4->5nday [day] <dur> <per> <idf> <nhead> N S NOM @<SUBJ #5->2n! [!] PU @PU #6->0n</s>n<ß>nI [I] <*> PERS 1S NOM @SUBJ> #1->2nspent [spend] <cjt-head> <mv> V IMPF @FS-STA #2->0nquality [quality] <f-q> <f-phys> <comp1> <first> <idf> <comp1> <ncomp> N S NOM @>N #3->4ntime [time] <ac-cat> <temp> <per> <num+> <second> <comp2> <idf> <nhead> N S NOM @<ACC #4->2nwith [with] PRP @<ADVL #5->2nmy [I] <poss> <refl> <det> PERS 1S GEN @>N #6->7nparents [parent] <Hfam> <def> <nhead> N P NOM @P< #7->5n, [,] PU @PU #8->0nand [and] <clb?> <co-fin> KC @CO #9->2nthe [the] <def> ART S/P @>N #10->12nMcDonald [McDonald] <*> <Proper> <first> <ncomp> N S NOM @>N #11->12nrestaurant [restaurant] <inst> <second> <def> <nhead> N S NOM @SUBJ> #12->13nwas [be] <cjt> <mv> V IMPF 1/3S @FS-STA #13->2nexcellent [excellent] <Q:good> ADJ POS @<SC #14->13n, [,] PU @PU #15->0ntoo [too] ADV @<ADVL #16->13n. [.] PU @PU #17->0n</s>n<ß>nI-m [I-m] <*> <unit> <ac-sign> <heur> <idf> <nhead> N S NOM @SUBJ> #1->2nlooking [look] <mv> V PCP1 @ICL-ADVL #2->0nforward [forward] <adir> <advl-close> ADV @<ADVL #3->2nto [to] <advl-close> PRP @<ADVL #4->2nseeing [see] <vq> <v.contact> <vtk+ADJ> <mv> V PCP1 @ICL-P< #5->4nthem [they] PERS 3P ACC @<ACC #6->5nagain [again] <atemp> ADV @<ADVL #7->5n! [!] PU @PU #8->0n</ß>”

“SRL_tagging”: {

“SRL_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“SRL_tagging_result”: “Today/ARG1 was/PRED (a wonderful day)/ARG2 ! I/ARG0 spent/PRED (quality time)/ARG1 (with my parents)/ARG2, and (the McDonald restaurant)/ARG1 was/PRED excellent/ARG2, too/ARGM-ADV. I/ARG0’m looking/PRED forward/ARGM-DIR (to seeing them again)/ARG1!”

}

Sentence 2: I’m really excited about Christmas! This year, my girlfriend and I are gonna celebrate the holiday together. We’re gonna decorate our room, and it’ll be so much fun!

{

“meaning”: {

“POS_tagging”: {

“POS_tagging_set”: “CST’s Part-Of-Speech tagger (Brill, with adaptations)”,

“POS_tagging_result”: ” I’m/NNP really/RB excited/VBD about/IN Christmas/NNP !/.nThis/DT year/NN ,/, my/PRP$ girlfriend/NN and/CC I/PRP are/VBP gon/VBG na/TO celebrate/VB the/DT holiday/NN together/RB ./. We’re/NNP gon/VBG na/TO decorate/VB our/PRP$ room/NN ,/, and/CC it’ll/NN be/VB so/RB much/JJ fun/NN !/.”

“NE_tagging”: {

“NE_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“NE_tagging_result”: ” I’m really excited about Christmas/DATE ! This year, my girlfriend and I are gonna celebrate the holiday together. We’re gonna decorate our room, and it’ll be so much fun! “

“dependency_tagging”: {

“dependency_tagging_set”: “CG-dependency, https://edu.visl.dk/visl/en/parsing/automatic/dependency.php “,

” dependency_tagging_result”: “n<ß>nI-m [I-m] <*> <unit> <ac-sign> <heur> <idf> <nhead> N S NOM @NPHR #1->0nreally [really] <ly> <ameta> <ADJ:real+ly> ADV @>A #2->3nexcited [excited] <np-close> ADJ POS @N< #3->1nabout [about] <pp-temp> PRP @A< #4->3nChristmas [Christmas] <*> <temp> <per> <nhead> N S NOM @P< #5->4n! [!] PU @PU #6->0n</s>n<ß>nThis [this] <*> <dem> DET S @>N #1->2nyear [year] <per> <dur> <def> <nhead> N S NOM @ADVL> #2->10n, [,] PU @PU #3->0nmy [I] <poss> <det> PERS 1S GEN @>N #4->5ngirlfriend [girlfriend] <cjt-head> <Hfam> <def> <nhead> N S NOM @SUBJ> #5->8nand [and] <co-subj> KC @CO #6->5nI [I] <cjt> <*> PERS 1S NOM @SUBJ> #7->5nare [be] <vch> <aux> V PR -1/3S @FS-STA #8->0ngonna [going=to] <complex> <aux> V PCP1 @ICL-AUX< #9->8ncelebrate [celebrate] <mv> V INF @ICL-AUX< #10->9nthe [the] <def> ART S/P @>N #11->12nholiday [holiday] <temp> <per> <def> <nhead> N S NOM @<ACC #12->10ntogether [together] ADV @<ADVL #13->10n. [.] PU @PU #14->0n</s>n<ß>nWe-re [We-re] <*> <Hmyth> <rem> <heur> <idf> <nhead> N S NOM @SUBJ> #1->3ngonna [going=to] <cjt-head> <complex> <aux> V PCP1 @FS-STA #2->0ndecorate [decorate] <v.contact> <mv> V INF @ICL-AUX< #3->2nour [we] <poss> <det> PERS GEN 1P @>N #4->5nroom [room] <Lh> <am> <def> <nhead> N S NOM @<ACC #5->3n, [,] PU @PU #6->0nand [and] <clb?> KC @CO #7->5nit-ll [it-ll] <heur> <idf> <nhead> N S NOM @SUBJ> #8->9nbe [be] <cjt> <mv> V SUBJ @FS-STA #9->2nso [so] <aquant> ADV @>A #10->11nmuch [much] <quant> DET ABS S @>N #11->12nfun [fun] <sem-c> <percep-f> <idf> <nhead> N S NOM @<SC #12->9n! [!] PU @PU #13->0n</ß>”

“SRL_tagging”: {

“SRL_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“SRL_tagging_result”: ” I/ARG1 ’m/PRED (really excited about Christmas)/ARG2! This year, (my girlfriend and I) /ARG0 are gonna celebrate/PRED (the holiday)/ARG1 together/ARGM-MNR. We/ARG0 ’re gonna decorate/PRED (our room)/ARG1, and it/ARG1 ’ll/ARGM-MOD be/PRED (so much fun)/ARG2 !”

}

Sentence 3: Today I watched a movie called ‘The Pianist.’ It was not only touching, but really absorbing, too. Now I’m feeling really happy, thanks to this memorable experience.

{

“meaning”: {

“POS_tagging”: {

“POS_tagging_set”: “CST’s Part-Of-Speech tagger (Brill, with adaptations)”,

“POS_tagging_result”: ” Today/RB I/PRP watched/VBD a/DT movie/NN called/VBN ‘/” The/DT Pianist/NNP ./. ‘/POS It/PRP was/VBD not/RB only/RB touching/VBG ,/, but/CC really/RB absorbing/VBG ,/, too/RB ./.nNow/RB I’m/NNP feeling/NN really/RB happy/JJ ,/, thanks/NNS to/TO this/DT memorable/JJ experience/NN ./.”

“NE_tagging”: {

“NE_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“NE_tagging_result”: ” Today I watched a movie called ‘The Pianist.’/WORK_OF_ART It was not only touching, but really absorbing, too. Now I’m feeling really happy, thanks to this memorable experience.”

“dependency_tagging”: {

“dependency_tagging_set”: “CG-dependency, https://edu.visl.dk/visl/en/parsing/automatic/dependency.php “,

” dependency_tagging_result”: “n<ß>nToday [today] <*> <atemp> ADV @ADVL> #1->3nI [I] <*> PERS 1S NOM @SUBJ> #2->3nwatched [watch] <DL:bio> <mv> V IMPF @FS-STA #3->0na [a] <indef> ART S @>N #4->5nmovie [movie] <sem-w> <DL:bio> <idf> <nhead> N S NOM @<ACC #5->3ncalled [call] <vtk+N> <vtk+ADJ> <vtk+N> <vtk+PROP> <vq> <v.contact> <DL:bio> <mv> <np-close> V PCP2 PAS @ICL-N< #6->5n-The [-The] <heur> <DL:bio> <idf> <nhead> N S NOM @<SC #7->6nPianist [Pianist] <*> <Proper> <DL:bio> <nhead> N S NOM @<OC #8->6n. [.] PU @PU #9->0n<ß>n- [-] PU @PU #1->0n</ß>n</s>n<ß>nIt [it] <*> PERS NEU 3S NOM @SUBJ> #1->2nwas [be] <DL:bio> <mv> V IMPF 1/3S @FS-STA #2->0nnot [not] ADV @>A #3->4nonly [only] <ly> <ADJ:on+ly> <advl-close> ADV @<ADVL #4->2ntouching [touching] <DL:bio> ADJ POS @<SC #5->2n, [,] PU @PU #6->0nbut [but] KC @CO #7->5nreally [really] <ly> <ameta> <ADJ:real+ly> ADV @ADVL> #8->9nabsorbing [absorb] <v.contact> <DL:bio> <mv> V PCP1 @ICL-N<PRED #9->1n, [,] PU @PU #10->0ntoo [too] <advl-close> ADV @<ADVL #11->9n. [.] PU @PU #12->0n</s>n<ß>nNow [now] <*> <atemp> ADV @ADVL #1->0nI-m [I-m] <*> <unit> <ac-sign> <DL:bio> <heur> <nhead> N S NOM @NPHR #2->1nfeeling [feel] <v.contact> <v-cog> <DL:bio> <mv> <np-close> V PCP1 @ICL-N<PRED #3->2nreally [really] <ly> <ameta> <ADJ:real+ly> ADV @>A #4->5nhappy [happy] <jpsych> <DL:bio> ADJ POS @<SC #5->3n, [,] PU @PU #6->0nthanks to [thanks=to] <insertion> <complex> PRP @<ADVL #7->3nthis [this] <dem> DET S @>N #8->10nmemorable [memorable] <DL:bio> ADJ POS @>N #9->10nexperience [experience] <f-psych> <percep-f> <DL:bio> <def> <nhead> N S NOM @P< #10->7n. [.] PU @PU #11->0n</ß>”

“SRL_tagging”: {

“SRL_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“SRL_tagging_result”: “Today/ARG-TMP I/ARG0 watched/PRED a movie/ARG1 called/PRED ‘The Pianist.’ It/ARG1 was/PRED (not only touching, but really absorbing, too)/ARG2. Now/ARG-TMP I/ARG0 ’m feeling/PRED (really happy)/ARG1, thanks to this memorable experience.”

}

6 Question Text Files

Q1: What is the tool in the picture?

Q2: What is the nickname of the person in the picture?

Q3: What is the job of the person on the left hand-side in the picture

Q4: What is the family name of the person in the centre of the picture?

Q5: What is the name of the square in the picture?

7 Question Speech Files

8 Images for Question

Images for Q1	Q1-1.jpg Q1-2.jpg Q1-3.jpg
Image for Q2	Q2-Joseph Gordon Levitt.jpg
Image for Q3	Q3-1.jpg Q3-2.jpg
images for Q4	Q4-1.jpg Q4-2.jpg Q4-3.jpg
1 image for Q5	Q5-1.jpg

9 Meaning JSON Files

Sentence 1: What is the tool in the picture?

{

“meaning”: {

“POS_tagging”: {

“POS_tagging_set”: “CST’s Part-Of-Speech tagger (Brill, with adaptations), https://cst.dk/online/pos_tagger/uk/”,

“POS_tagging_result”: “What/WP is/VBZ the/DT tool/NN in/IN the/DT picture/NN ?/.”

“NE_tagging”: {

“NE_tagging_set”: “CST’s named entity recogniser, https://cst.dk/online/navnegenkenderCSTNER/uk/”,

“NE_tagging_result”: ” [What,misc,uncertain] is the tool in the picture ?”

“dependency_tagging”: {

“dependency_tagging_set”: “CG-dependency, https://edu.visl.dk/visl/en/parsing/automatic/dependency.php “,

” dependency_tagging_result”: “<ß>nWhat [what] <clb> <*> <interr> INDP S/P @SC> #1->2nis [be] <mv> V PR 3S @FS-QUE #2->0nthe [the] <def> ART S/P @>N #3->4ntool [tool] <tool> <def> <nhead> N S NOM @<SUBJ #4->2nin [in] <advl-fs> PRP @<ADVL #5->2nthe [the] <def> ART S/P @>N #6->7npicture [picture] <pict> <repr> <def> <nhead> N S NOM @P< #7->5n? [?] PU @PU #8->0n</ß>”

“SRL_tagging”: {

“SRL_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“SRL_tagging_result”: ” What/ARG2 is/PRED (the tool in the picture)/ARG1 ?”

}

Sentence 2: What is the nickname of the person in the picture?

What/WP is/VBZ the/DT nickname/NN of/IN the/DT person/NN in/IN the/DT picture/NN ?/.

{

“meaning”: {

“POS_tagging”: {

“POS_tagging_set”: “CST’s Part-Of-Speech tagger (Brill, with adaptations)”,

“POS_tagging_result”: ” What/WP is/VBZ the/DT nickname/NN of/IN the/DT person/NN in/IN the/DT picture/NN ?/.”

“NE_tagging”: {

“NE_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/ner.html “,

“NE_tagging_result”: “”

“dependency_tagging”: {

“dependency_tagging_set”: “CG-dependency, https://edu.visl.dk/visl/en/parsing/automatic/dependency.php “,

” dependency_tagging_result”: ” <ß>nWhat [what] <clb> <*> <interr> INDP S/P @SC> #1->2nis [be] <mv> V PR 3S @FS-QUE #2->0nthe [the] <def> ART S/P @>N #3->4nnickname [nickname] <ac-cat> <def> <nhead> N S NOM @<SUBJ #4->2nof [of] <np-close> PRP @N< #5->4nthe [the] <def> ART S/P @>N #6->7nperson [person] <H> <def> <nhead> N S NOM @P< #7->5nin [in] <advl-fs> PRP @<ADVL #8->2nthe [the] <def> ART S/P @>N #9->10npicture [picture] <pict> <repr> <def> <nhead> N S NOM @P< #10->8n? [?] PU @PU #11->0n</ß>”

“SRL_tagging”: {

“SRL_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“SRL_tagging_result”: ” What/ARG2 is/PRED (the nickname of the person in the picture)/ARG1 ?”

}

Sentence 3: What is the job of the person on the left hand-side in the picture?

{

“meaning”: {

“POS_tagging”: {

“POS_tagging_set”: “CST’s Part-Of-Speech tagger (Brill, with adaptations)”,

“POS_tagging_result”: ” What/WP is/VBZ the/DT job/NN of/IN the/DT person/NN on/IN the/DT left/VBN hand-side/JJ in/IN the/DT picture/NN ?/.”

“NE_tagging”: {

“NE_tagging_set”: ” https://cst.dk/online/navnegenkenderCSTNER/uk/”,

“NE_tagging_result”: ” [What,misc,uncertain] is the job of the person on the left hand-side in the picture ?”

“dependency_tagging”: {

“dependency_tagging_set”: “CG-dependency, https://edu.visl.dk/visl/en/parsing/automatic/dependency.php “,

” dependency_tagging_result”: ” <ß>nWhat [what] <clb> <*> <interr> INDP S/P @SC> #1->2nis [be] <mv> V PR 3S @FS-QUE #2->0nthe [the] <def> ART S/P @>N #3->4njob [job] <pos-soc> <sem-c> <def> <nhead> N S NOM @<SUBJ #4->2nof [of] <np-close> PRP @N< #5->4nthe [the] <def> ART S/P @>N #6->7nperson [person] <H> <def> <nhead> N S NOM @P< #7->5non [on] <advl-fs> PRP @<ADVL #8->2nthe [the] <def> ART S/P @>N #9->11nleft [left] ADJ POS @>N #10->11nhand-side [hand-side] <Lsurf> <HH> <geom> <heur> <def> <nhead> N S NOM @P< [hand-side] <heur> <def> N S NOM @P< #11->8nin [in] <advl-fs> PRP @<ADVL #12->2nthe [the] <def> ART S/P @>N #13->14npicture [picture] <pict> <repr> <def> <nhead> N S NOM @P< #14->12n? [?] PU @PU #15->0n</ß>”

“SRL_tagging”: {

“SRL_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“SRL_tagging_result”: ” What/ARG2 is/PRED (the job of the person on the left hand-side in the picture)/ARG1 ?”

}

Sentence 4: What is the family name of the person in the centre of the picture?

{

“meaning”: {

“POS_tagging”: {

“POS_tagging_set”: “CST’s Part-Of-Speech tagger (Brill, with adaptations)”,

“POS_tagging_result”: ” What/WP is/VBZ the/DT family/NN name/NN of/IN the/DT person/NN in/IN the/DT centre/NN of/IN the/DT picture/NN ?/.”

“NE_tagging”: {

“NE_tagging_set”: ” https://cst.dk/online/navnegenkenderCSTNER/uk/”,

“NE_tagging_result”: ” [What,misc,uncertain] is the family name of the person in the centre of the picture ?”

“dependency_tagging”: {

“dependency_tagging_set”: “CG-dependency, https://edu.visl.dk/visl/en/parsing/automatic/dependency.php “,

” dependency_tagging_result”: ” <ß>nWhat [what] <clb> <*> <interr> INDP S/P @SC> #1->2nis [be] <mv> V PR 3S @FS-QUE #2->0nthe [the] <def> ART S/P @>N #3->5nfamily [family] <HH> <comp1> <comp1> <ncomp> N S NOM @>N #4->5nname [name] <ac-cat> <comp2> <def> <nhead> N S NOM @<SUBJ #5->2nof [of] <np-close> PRP @N< #6->5nthe [the] <def> ART S/P @>N #7->8nperson [person] <H> <def> <nhead> N S NOM @P< #8->6nin [in] <advl-fs> PRP @<ADVL #9->2nthe [the] <def> ART S/P @>N #10->11ncentre [centre] <Labs> <inst> <def> <nhead> N S NOM @P< #11->9nof [of] <np-close> PRP @N< #12->11nthe [the] <def> ART S/P @>N #13->14npicture [picture] <pict> <repr> <def> <nhead> N S NOM @P< #14->12n? [?] PU @PU #15->0n</ß>”

“SRL_tagging”: {

“SRL_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“SRL_tagging_result”: ” What/ARG2 is/PRED (the family name of the person in the centre of the picture)/ARG1 ?”

}

Sentence 5: What is the name of the square in the picture?

{

“meaning”: {

“POS_tagging”: {

“POS_tagging_set”: “CST’s Part-Of-Speech tagger (Brill, with adaptations)”,

“POS_tagging_result”: ” What/WP is/VBZ the/DT name/NN of/IN the/DT square/NN of/IN the/DT picture/NN ?/.”

“NE_tagging”: {

“NE_tagging_set”: ” https://cst.dk/online/navnegenkenderCSTNER/uk/”,

“NE_tagging_result”: “[What,misc,uncertain] is the name of the square of the picture ?”

“dependency_tagging”: {

“dependency_tagging_set”: “CG-dependency, https://edu.visl.dk/visl/en/parsing/automatic/dependency.php “,

” dependency_tagging_result”: ” n<ß>nWhat [what] <clb> <*> <interr> INDP S/P @SC> #1->2nis [be] <mv> V PR 3S @FS-QUE #2->0nthe [the] <def> ART S/P @>N #3->4nname [name] <ac-cat> <sem-c> <def> <nhead> N S NOM @<SUBJ #4->2nof [of] <np-close> PRP @N< #5->4nthe [the] <def> ART S/P @>N #6->7nsquare [square] <Lh> <geom> <def> <nhead> N S NOM @P< #7->5nof [in] <np-close> PRP @N< #8->7nthe [the] <def> ART S/P @>N #9->10npicture [picture] <pict> <repr> <def> <nhead> N S NOM @P< #10->8n? [?] PU @PU #11->0n</ß>”

“SRL_tagging”: {

“SRL_tagging_set”: “HanLP, https://hanlp.hankcs.com/en/demos/srl.html”,

“SRL_tagging_result”: ” What/ARG2 is/PRED (the name of the square of the picture)/ARG1 ?”

}

10 Intention JSON Files

Q1: What is the tool in the picture?

{

“Intention”:{

“qtopic”: “tool”,

“qfocus”:”What”,

“qLAT”:”tool”,

“qSAT”:”ETC”,

qdomain”:”everyday life”

}

Q2: What is the nickname of the person in the picture?

{

“Intention”: {

“qtopic”: “person”,

“qfocus”:”What”,

“qLAT”:”nickname”,

“qSAT”:”PS_NAME”,

“qdomain”:”famous people”

}

Q3: What is the job of the person on the left hand-side in the picture

{

“Intention”:{

“qtopic”:”person”,

“qfocus”:”What”,

“qLAT”:”job”,

“qSAT”:”CV_OCCUPATION”,

“qdomain”:”famous people”

}

Q4: What is the family name of the person in the centre of the picture?

{

“Intention”:{

“qtopic”:”person”,

“qfocus”:”What”,

“qLAT”:”family name”,

“qSAT”:”PS_NAME”,

“qdomain”:”famous people”

}

Q5: What is the name of the square in the picture?

{

“Intention”:{

“qtopic”:”square”,

“qfocus”:”What”,

“qLAT”:”square”,

“qSAT”:”LC_TOUR”,

“qdomain”:”traveling”

}

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1 Introduction

2 Text with Emotion

2.1 Coherent scenarios

2.2 Incoherent scenarios

3 Audio and Video with Emotion

3.1 Neutral

3.2 Angry

3.3 Happy

3.4 Incoherent

4 Emotion JSON Files

5 Meaning JSON Files

6 Question Text Files

7 Question Speech Files

8 Images for Question

9 Meaning JSON Files

10 Intention JSON Files

Notice