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



*********************************************************************************
id_87T_2
Ratio of Tags per Word for Sentence no: 6
Word Ambiguity Ratio: 1.16667
Lookahead Start Active Chart
0-[n-Soto_Toro] 1-[v-invented] 2-[d-a] 3-[d-3/D] 4-[d-measuring_system, n-measuring_system] 5-[x- .] 


0-[n-Soto_Toro] 1-[v-invented] 2-[d-a] 3-[d-3/D] 4-[d-measuring_system, n-measuring_system] 5-[x- .] 


PennTreebank Style Tagging

6
Soto_Toro-nnp
invented-vbd
a-dt
3/D-cd
measuring_system-nn
. - punto

Tagging and Syntactic Constituency

[Soto_Toro-n, invented-vin, a-art, 3/D-num, measuring_system-n, . - punto]

f-[subj-[Soto_Toro-n-sn], ibar-[invented-vppt-sv3], sn-[a-art-sn, 3/D-num-sn, measuring_system-n-sn], cp-[. - punto-cp]] 

6


Functional and Syntactic Constituency

subj-[Soto_Toro-n-sn]
ibar-[invented-vppt-sv3]
obj-[a-art-sn, 3/D-num-sn, measuring_system-n-sn]

Output of Anaphora Resolution Module

all_prons([1-[]])
main  resolved as  Soto_Toro  with semantic index  id2
second  resolved as  measuring_system  with semantic index  id5

############   TOPICS   ############
MAIN TOPIC:  'Soto_Toro'
SECONDARY TOPIC:  measuring_system


Augmented Head Dependent Indexed Structures

det(measuring_system-sn2, a).
mod(sn2, measuring_system, '3/D').
'obj-product'(invent-cl5, measuring_system-sn2).
'subj-agent'(invent-cl5, 'Soto_Toro'-sn1).
tense(past, '_', invent).
voice(active, '_', invent).

Semantic Interpretation and Informational Structure

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


id_87T_2
Discourse Relations and Discourse Structure

sd_structure(id_87T_2, 7, objective, cause, past, invent, foreground, down, down(5-7))
p_o_view:narrator

