Slides for my presentation in Turin

1. ITVENSES - A SYMBOLIC
SYSTEM FOR ASPECT
BASED SENTIMENT
ANALYSIS
RODOLFO DELMONTE
DIPARTIMENTO DI STUDI LINGUISTICI E CULTURALI COMPARATI
UNIVERSITÀ CA’ FOSCARI
EMAIL: DELMONT@UNIVE.IT WEBSITE: RONDELMO.IT
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2. OUTLINE
• Systems’ Architectures
• A Walkthrough Example
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3. ITGETARUNS
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4. ITVENSES
To develop the system I used 20% of the dataset and the remaining 80% for testing
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5. WALKTHROUGH EXAMPLE
TAGGING AND LEMMATIZING
• opn(1240342904,[0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"M
anca il dentifricio in bagno.").
• 1240342904_1 - ['Manca'-v,il-art,dentifricio-n,in-p,bagno-n,'.'-
punto],
• 1240342904_1-[ i(1,’Manca',v,mancare-[sems=intr,mfeats=kl3s]),
i(2,il,art,il-[sems=def,mfeats=ms]), i(3,dentifricio,n,dentifricio-
[mfeats=ms]), i(4,in,p,in), i(5,bagno,n,bagno-
[sems=com,mfeats=ms]), i(6,’.',[punto],-)
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6. WALKTHROUGH EXAMPLE
SYNTAX & SEMANTICS
• 1240342904_1-[ ibar-[‘Manca'-v-sn], obj-[il-art-sn,dentifricio-n-sn],
obl-[in-p-sp,bagno-n-sn]]
• 1240342904_1-[
• bagno-obl-1-[obl-[in-p-sp,bagno-n-sn]],
• dentifricio-obj-1-[obj-[il-art-sn,dentifricio-n-sn]],
• mancare-ibar-1- ibar-[Manca-v-sn]
• ]
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7. WALKTHROUGH EXAMPLE
SYNTAX & SEMANTICS
pas(1240342904_1, mancare - [ refex(1240342904_1-1, v, 'Manca' -
mancare, [sems=intr,mfeats=kl3s], [activ,not_exten]),
refex(1240342904_1-3, n, dentifricio-dentifricio, [3,mas,sing],
[mfeats=ms], 1, subj / theme),
[ i(4,in,p,in,sp,[],1,-), refex(1240342904_1-5, n, bagno - bagno,
[def=indef,3,mas,sing], [
[act,agnt,artf,bld,cse,dyn,liqd,locat,med,obj,part], polsem = neut], 4,
obl / theme) ]
1 - [ lemma = mancare, disc_m = nil, polsem = negative, subcat =
[activ-not_exten], parola = ‘Manca’, change = gradual, view = external,
factive = factive, moodtense = presente] )
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8. WALKTHROUGH EXAMPLE
FROM ITGETARUNS TO ITVENSES
• Try Match Aspect/s from refexs, i.e. Nouns, Verbs,
Adjectives - bagno aspect 2; mancare aspect 3
• Try Match Polarity/ies from refexs, i.e. Nouns,
Verbs, Adjectives - mancare marked as negative
• sievesall: recomposes aspects and polarities which
can be multiple for every sentence in a text
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9. WALKTHROUGH EXAMPLE
FROM ITGETARUNS TO ITVENSES
• sievescheck: invertpols (invert polarities for the current aspect)
• sievescheck: focalizers (spots focalizers, minimizers, downtoners)
• sievescheck: checknegpriv (finds negation and its scope)
• sievescheck: syntax sieves (deletes current aspect assignment identifiers)
• Ind=2;Ind=3;Ind=6;Ind=7 - bagno Ind=2 (deleted)
• Ind=3 albergo;hotel;struttura & centro;centrale;a_due_passi
• Ind=2 camera;moquet;asciugamano;stanza;ambiente;bagno;letto &
spazioso;comodo & + pulito
• Ind=7 strada;piazza & rumoroso
• Ind=7 arrivare;raggiungere & difficile;distante;scomodo;scarso
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10. WALKTHROUGH EXAMPLE
• collapseall: recovers all clause level analysis of the current
sentence both at propositional and at subjective/factivity level and
collects them together
• now each evaluation term is made up by a text index - a set of
semantic propositional level representations for that sentence - one
aspect assignment - one associated polarity assignment, made up
by a positive and a negative slot
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11. WALKTHROUGH EXAMPLE
AUGMENTED PREDICATE ARGUMENT STR.
• 1240342904-[
• 1240342904_1-mancare(neg,statement,dentifricio-dentifricio-3,
bagno-bagno-5)]-
• [mancare]- Aspect seeds
• [[],[Manca]]- Polarities: Positive+Negative
• 3] Aspect Identifier
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12. WALKTHROUGH EXAMPLE
• evalothers: evaluates sentences marked with aspect n.8 and
associates semantic representations
• reduceevals: collapses evaluation terms for the same sentence
with identical values
• othersieve: sieves and modifies aspect value using combinations
of aspect assignments present at text level; fires preferences for
combined aspect values which modify one or more value
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13. WALKTHROUGH EXAMPLE
• comparevals: sieves and modifies those texts declaring “tutto bene”
or the opposite with an all aspects positive/negative marking
• checks for texts made up by a couple of aspects each evaluated to
the contrary
• checks for texts which have a semantic propositional level analysis
as nonfactual or as negated and marks them with negative polarity -
if + double negations
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14. WALKTHROUGH EXAMPLE
• Outputs the resulting 0/1 string
• 1240342904-[0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]-true
www.rondelmo.it
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15. PERFORMANCE OF ITVENSES
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Delayed Results for Test Set After Ablation Experiment

16. PERFORMANCE OF ITVENSES
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Results for Development Set

17. PERFORMANCE OF ITVENSES
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Published Results for Test Set

18. ITVENSES FOR IRONITA
TASK A: Binary classification
TASK B: Multiclass classification
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