
**************************



*********************************************************************************
id_204T_2
Ratio of Tags per Word for Sentence no: 6
Word Ambiguity Ratio: 1.2
Lookahead Start Active Chart
0-[n-Alberto_Tomba] 1-[n-won, v-won] 2-[d-a] 3-[n-ski_race] 4-[x- .] 


New Ratio of Tags per Word after FSA Disambiguation: 
1
0-[n-Alberto_Tomba] 1-[v-won] 2-[d-a] 3-[n-ski_race] 4-[x- .] 

0-[n-Alberto_Tomba] 1-[v-won] 2-[d-a] 3-[n-ski_race] 4-[x- .] 


PennTreebank Style Tagging

6
Alberto_Tomba-nnp
won-vbd_vbn
a-dt
ski_race-nn
. - punto

Tagging and Syntactic Constituency

[Alberto_Tomba-n, won-vt, a-art, ski_race-n, . - punto]

f-[sn-[Alberto_Tomba-n-sn], ibar-[won-vppt-sv3], sn-[a-art-sn, ski_race-n-sn], cp-[. - punto-cp]] 

6


Functional and Syntactic Constituency

subj-[Alberto_Tomba-n-sn]
ibar-[won-vppt-sv3]
obj-[a-art-sn, ski_race-n-sn]

Output of Anaphora Resolution Module

all_prons([1-[]])
main  resolved as  Alberto_Tomba  with semantic index  id1
second  resolved as  ski_race  with semantic index  id5

############   TOPICS   ############
MAIN TOPIC:  'Alberto_Tomba'
SECONDARY TOPIC:  ski_race


Augmented Head Dependent Indexed Structures

det(ski_race-sn2, a).
'obj-theme_aff'(win-cl8, ski_race-sn2).
'subj-agent'(win-cl8, 'Alberto_Tomba'-sn1).
tense(past, '_', win).
voice(active, '_', win).

Semantic Interpretation and Informational Structure

[7, indirect, win, past, active, nil, nil, nil, indic, nil, attivita]
sinfo(7, main/prop, external, factive, culminated, foreground, attivita, win, past, narration, objective, nil)


id_204T_2
Discourse Relations and Discourse Structure

sd_structure(id_204T_2, 7, objective, narration, past, win, foreground, level, down(5-7))
p_o_view:narrator

