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:
Well we have been working with Ulistic for 1.5 months, and have 100 people following our site on Facebook, and our web site, www.designofashion.com has seen a 3 fold increase in traffic, which is significantly beating our expectations - SEO is a process that takes time and to get results this quickly is exceptional.
Postion	Tokenization
1	Well
2	we
3	have
4	been
5	working
6	with
7	Ulistic
8	for
9	1.5
10	months
11	,
12	and
13	have
14	100
15	people
16	following
17	our
18	site
19	on
20	Facebook
21	,
22	and
23	our
24	web
25	site
26	,
27	www.designofashion.com
28	has
29	seen
30	a
31	3
32	fold
33	increase
34	in
35	traffic
36	,
37	which
38	is
39	significantly
40	beating
41	our
42	expectations
43	-
44	SEO
45	is
46	a
47	process
48	that
49	takes
50	time
51	and
52	to
53	get
54	results
55	this
56	quickly
57	is
58	exceptional
59	.
Position	Tokenization	UPOS	Head	Deprel
1	Well	INTJ	5	discourse
2	we	PRON	5	nsubj
3	have	AUX	5	aux
4	been	AUX	5	aux
5	working	VERB	0	root
6	with	ADP	7	case
7	Ulistic	PROPN	5	obl
8	for	ADP	10	case
9	1.5	NUM	10	nummod
10	months	NOUN	5	obl
11	,	PUNCT	13	punct
12	and	CCONJ	13	cc
13	have	VERB	5	conj
14	100	NUM	15	nummod
15	people	NOUN	13	obj
16	following	VERB	15	acl
17	our	PRON	18	nmod:poss
18	site	NOUN	16	obj
19	on	ADP	20	case
20	Facebook	PROPN	16	obl
21	,	PUNCT	29	punct
22	and	CCONJ	29	cc
23	our	PRON	25	nmod:poss
24	web	NOUN	25	compound
25	site	NOUN	29	nsubj
26	,	PUNCT	25	punct
27	www.designofashion.com	X	25	appos
28	has	AUX	29	aux
29	seen	VERB	5	conj
30	a	DET	33	det
31	3	NUM	32	nummod
32	fold	NOUN	33	compound
33	increase	NOUN	29	obj
34	in	ADP	35	case
35	traffic	NOUN	33	nmod
36	,	PUNCT	33	punct
37	which	PRON	40	nsubj
38	is	AUX	40	aux
39	significantly	ADV	40	advmod
40	beating	VERB	33	acl:relcl
41	our	PRON	42	nmod:poss
42	expectations	NOUN	40	obj
43	-	PUNCT	5	punct
44	SEO	NOUN	47	nsubj
45	is	AUX	47	cop
46	a	DET	47	det
47	process	NOUN	40	parataxis
48	that	PRON	49	nsubj
49	takes	VERB	47	acl:relcl
50	time	NOUN	49	obj
51	and	CCONJ	58	cc
52	to	PART	53	mark
53	get	VERB	58	csubj
54	results	NOUN	53	obj
55	this	ADV	56	advmod
56	quickly	ADV	53	advmod
57	is	AUX	58	cop
58	exceptional	ADJ	47	conj
59	.	PUNCT	5	punct