As a helpful and smart assistant, your task is to parse a given text in any language to Universal Dependency (UD) format including POS tags and dependency relations (HEAD and DEPREL).
Key Components of UD Annotation:
1. Tokens: The fundamental units within UD are tokens. These can be individual words, punctuation marks, or even parts of multi-word expressions. Each token has several associated attributes.
2. UPOS Tags: The UPOS field in the CoNLL-U format represents the universal part-of-speech tag assigned to each word. This tag is part of a universal POS tag set designed to be applicable across different languages. The UPOS tags include categories such as NOUN, VERB, ADJ (adjective), ADV (adverb), PRON (pronoun), DET (determiner), and more. 
3. Dependency Relations: Dependency relations are the core of the syntactic representation. They form a tree structure over the tokens in a sentence. Here's how they work:
    - HEAD: This field indicates the head of the current word. The head is the word that the current word is connected to in the dependency parse tree. The value is an integer that corresponds to the ID of the head word within the same sentence. A value of zero (0) indicates that the word is the root of the sentence.
    - DEPREL: The DEPREL field specifies the type of dependency relation between the current word and its head (as specified in the HEAD field). The value is a universal dependency relation or a language-specific subtype of such a relation.
Note: Blank lines are used to mark the boundaries between sentences.
Example:
Let's analyze this sentence with its UD annotation:
"The big dog chased the cat."
1. Tokenization:
- The
- big
- dog
- chased
- the
- cat
- .
2. UPOS Tags:
- The: DET
- big: ADJ
- dog: NOUN
- chased: VERB
- the: DET
- cat: NOUN
- .: PUNCT
3. Head node (parent):
- The: the parent of this word is "dog" at position 3
- big: the parent of this word is "dog" at position 3
- dog: the parent of this word is "chased" at position 4
- chased: this is the root node, therefore its head is 0
- the: the parent of this word is "cat" at position 6
- cat: the parent of this word is "chased" at position 4
- .: the parent of this word is "chased" at position 4
3. Dependency Relations:
- root(ROOT, chased)
- det(dog, The)
- amod(dog, big)
- nsubj(chased, dog)
- det(cat, the)
- obj(chased, cat)
Combining the above annotations, the final output in UD format is:
Position	Tokenization	UPOS	Head	Deprel
1	The	DET	3	det
2	big	ADJ	3	amod
3	dog	NOUN	4	nsubj
4	chased	VERB	0	ROOT
5	the	DET	6	det
6	cat	NOUN	4	obj
7	.	PUNCT	4	punct
Generate UD annotations for the following tokenized text:
With luck, the Kashmir Valley can attract investment from the Middle East and other locations where Muslims are dominant and become a tourist, education and services haven within India.
Postion	Tokenization
1	With
2	luck
3	,
4	the
5	Kashmir
6	Valley
7	can
8	attract
9	investment
10	from
11	the
12	Middle
13	East
14	and
15	other
16	locations
17	where
18	Muslims
19	are
20	dominant
21	and
22	become
23	a
24	tourist
25	,
26	education
27	and
28	services
29	haven
30	within
31	India
32	.
Position	Tokenization	UPOS	Head	Deprel
1	With	ADP	2	case
2	luck	NOUN	8	obl
3	,	PUNCT	8	punct
4	the	DET	6	det
5	Kashmir	PROPN	6	compound
6	Valley	PROPN	8	nsubj
7	can	AUX	8	aux
8	attract	VERB	0	root
9	investment	NOUN	8	obj
10	from	ADP	13	case
11	the	DET	13	det
12	Middle	PROPN	13	compound
13	East	PROPN	9	nmod
14	and	CCONJ	16	cc
15	other	ADJ	16	amod
16	locations	NOUN	13	conj
17	where	SCONJ	20	mark
18	Muslims	PROPN	20	nsubj
19	are	AUX	20	cop
20	dominant	ADJ	16	acl:relcl
21	and	CCONJ	22	cc
22	become	VERB	8	conj
23	a	DET	29	det
24	tourist	NOUN	29	compound
25	,	PUNCT	26	punct
26	education	NOUN	24	conj
27	and	CCONJ	28	cc
28	services	NOUN	24	conj
29	haven	NOUN	22	xcomp
30	within	ADP	31	case
31	India	PROPN	29	nmod
32	.	PUNCT	8	punct