1. Preposition Phrase Attachment in English Language Analysis
Ashish Almeida
03M05601

2. PP attachment John read the report on new technologies. read John the
PP attached to NP
the report
PP attached to VP *
December 28, 2018
CFILT,IIT Bombay

3. Same Structure: different roles
Ram ate rice with a spoon. -instrument
spoon(icl>tool))
Ram ate rice with Sita. -co-agent
Sita(iof>person))
December 28, 2018
CFILT,IIT Bombay

4. UNL and EnConvertor
UNL is an intermediate language for representing meaning of natural language.
EnConvertor is a language independent parser
Rules are written for analysis
UW Dictionary is created for analysis
PP-attachment is handled in EnCo.
December 28, 2018
CFILT,IIT Bombay

5. More about UNL UNL graph of John eats rice with a spoon eat(icl>do)
ins
spoon(icl>artifact)
@ entry.
@ present
obj
rice(icl>food)
agt
John(iof>person)
December 28, 2018
CFILT,IIT Bombay

6. Adjuncts It provides extra information in a sentence.
It attaches to the verb.
Examples:
Ram came home.
Ram came home on Monday.
Sita is sleeping.
Sita is sleeping in the room.
December 28, 2018
CFILT,IIT Bombay

7. Temporal Prepositional Phrases
Represents temporal information with the help of an object
e.g. on Sunday , for two days, at 5 p.m., on Diwali,
in ice age, after the meeting, till 6 O’ clock,
over two hours, beyond midnight
Prepositions that can show temporality at
over
through
before
for
since by in
from
during
beyond
till
until to on
after
between
inside
into
within of
December 28, 2018
CFILT,IIT Bombay

8. Time attributes To identify the type of time word e.g. Attribute
Examples
TIME
Today, March
UNIT
Day, second
EVENT
Morning, Dinner
TIM_TOKEN
am, pm
SECOND*
12, 15
DAY*
Sunday; 23
POFDAY
Dinner, Sunset
WEEK
Week
ZDIM
Start, End, Middle
December 28, 2018
CFILT,IIT Bombay

9. UNL of Temporal PPs Different UNL generation in two different cases
Delete the preposition
e.g. come at noon
tim(come , noon)
Retain the preposition
e.g. come before noon
tim(come, before)
obj(before,noon)
December 28, 2018
CFILT,IIT Bombay

10. Mapping from Prepositions to UNL relations
Attributes of the Arguments at
tim
[TIME,TIM_TOKEN] in
[N,TIME,MONTH]
[N,TIME,YEAR]
[N,POF_DAY] on
[N,TIME,DAY]
after
tim-obj
[N,TIME]
[N,EVENT]
before
December 28, 2018
CFILT,IIT Bombay

11. Rules Rules for at-PP - Applies to “at 6 pm” ;delete at
DL(VRB){PRE,#AT:::}{TIME,TIM_TOKEN:
+ATRES,+PRERES,+pTIM::}P22;
;create relation tim
<{VRB:::}{ATRES,PRERES,pTIM::tim:}P20;
December 28, 2018
CFILT,IIT Bombay

12. Testing Wall Street Journal (WSJ) corpus is used.
Sentences from Oxford advanced learner’s Dictionary are also tested.
WSJ has V-N-P-N four-word sentence fragments
All temporal cases are tested for correctness of UNL
December 28, 2018
CFILT,IIT Bombay

13. Results #Total PPs 20801 #Temporal PPs 1326 #Cases of correct UNL 1112
Average accuracy
83.9 %
Errors are mainly due to
mistakes in corpus and
inaccuracies in UW
dictionary
December 28, 2018
CFILT,IIT Bombay

14. Associative of-PP NP: the comedy of Shakespeare
mod(comedy(icl>abstract thing), Shakespeare(iof >person))
NP: the eyes of the boy
pof(boy(icl>person),
AP: guilty of an offence
obj(guilty(aoj>thing), offence(icl>abstract thing))
NP: book of Ram
pos(book(icl>concrete thing), Ram(iof>person))
December 28, 2018
CFILT,IIT Bombay

15. Partitive of-PP e.g. that kind of people mod(people, kind)
Here, in case of N1-OF-N2 the semantic head is the N2.
The first NP indicates a quantity
Examples
cup of tea qua(tea, cup)
bag of oranges
bundle of sticks
a pinch of salt
Kind construction
e.g. that kind of people mod(people, kind)
Kind-type words : kind, type, sort, variety etc.
December 28, 2018
CFILT,IIT Bombay

16. Argument structure (AS)
Argument structure specify the structural frame into which a verb can be fitted.
For example,
*Ram saw.
This is unacceptable as verb see has strict
subcategorisation feature (+ _NP). That is verb see
takes NP as object. Thus a valid sentence is
Ram saw Sita.
AS of see is (NP _ NP)
December 28, 2018
CFILT,IIT Bombay

17. Adjunct and Complements
He gave a book to Ram.
give (NP _ NP to-PP)
- without to Ram sentence is unacceptable
- to Ram is complement
He gave a book to Ram on Sunday
- without on Sunday sentence is acceptable
- on Sunday is adjunct
Similarly, nouns and adjectives take complements
December 28, 2018
CFILT,IIT Bombay

18. More on AS Ram accused Sita of cheating AS is (NP _ NP of-PP)
UNL for the sentence frame with the verb accuse (agtNP _ objNP rsnof-PP)
Whereas for adjuncts, the case relations differ.
He saw the girl through the window.
He saw the girl with anger.
He saw the girl in the library.
December 28, 2018
CFILT,IIT Bombay

19. Dictionary entry He gave a book to Ram.
The lexicon will have entry of gave which provides AS information.
[gave] {} “give(icl>do)” (VRB,VOA,VOA-PHSL,
#_TO, #_TO_GOL,PAST) <E,0,0>;
PP in the sentence can be identified as a complement or not.
This solves the attachment in some cases.
December 28, 2018
CFILT,IIT Bombay

20. Verb attachment of ‘of-PP’
Three possible cases V
NP1
NP2
V attaches to NP2
NP2 attaches to NP1
(C) V
NP1
NP2
V attaches to NP1
V attaches to NP2
(A) V
NP1
NP2
V attaches to NP1
NP1 attaches to NP2
(B)
December 28, 2018
CFILT,IIT Bombay

21. of-PP attachment cases
... remind him of Gita
Case A
... saw the book of physics
Case B
... drank a cup of milk
Case C
December 28, 2018
CFILT,IIT Bombay

22. Four cases of attachment
Attachment in presence or absence of attribute of
Attributes of V
Attributes of NP1
Attachment of NP2 1
V,OF
N,OF
NP1 2
V,^OF 3
N,^OF V 4
December 28, 2018
CFILT,IIT Bombay

23. Rules ;Noun attachment R{VRB,#_OF:::}{N,#_OF:::}(PRE,#OF)P60;
R{VRB,^#_OF:::}{N:::}(PRE,#OF)P60;
;Verb attachment, first resolve the immediate object
<{VRB,#_OF,#_OF_OBJ:::}{N,^#_OF::obj:}
(PRE,#OF)P30;
December 28, 2018
CFILT,IIT Bombay

24. Testing process British National Corpus (BNC) is used.
V-N-of-N type sentences are extracted from corpus.
AS information is added to verbs and nouns using Oxford Advanced Learner’s Dictionary and Beth Levin’s verb classes.
AS information is merged into the Dictionary.
December 28, 2018
CFILT,IIT Bombay

25. Results Total Correct Incorrect V-attachment 7 N-attachment (all) 493
N-attachment (all)
493
439 54
Associative cases
411
362 49
Partitive cases
82 (16%) 77 5
500
446
December 28, 2018
CFILT,IIT Bombay

26. To sum up
The PP attachment problem is successfully divided in two parts – complement PPs and adjunct PPs
This division clearly delineates the problem so that their analysis does not conflict.
Analysis of complements will be mostly driven by rich attribute set from lexicon
Whereas analysis of adjuncts will be driven by rules
December 28, 2018
CFILT,IIT Bombay

27. Contribution Deciding the overall strategy of analysis
Providing computation insights in linguistic analysis
Design of attribute set/introducing new attributes
Design and implementation of rules for EnCo.
Testing of sentences.
Dictionary corrections/modifications
December 28, 2018
CFILT,IIT Bombay

28. Future work Focus will be on complements.
Also, that-clause, to and -ing infinite clause handling, PRO detection will be tried in similar fashion.
Automatic/semi-automatic acquisition of AS information for dictionaries will be tried out.
December 28, 2018
CFILT,IIT Bombay