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:
I would rate Fran pcs an A+ because the price was lower than everyone else, i got my computer back the next day, and the professionalism he showed was great.
Postion	Tokenization
1	I
2	would
3	rate
4	Fran
5	pcs
6	an
7	A
8	+
9	because
10	the
11	price
12	was
13	lower
14	than
15	everyone
16	else
17	,
18	i
19	got
20	my
21	computer
22	back
23	the
24	next
25	day
26	,
27	and
28	the
29	professionalism
30	he
31	showed
32	was
33	great
34	.
Position	Tokenization	UPOS	Head	Deprel
1	I	PRON	3	nsubj
2	would	AUX	3	aux
3	rate	VERB	0	root
4	Fran	PROPN	5	compound
5	pcs	PROPN	3	obj
6	an	DET	7	det
7	A	SYM	3	xcomp
8	+	SYM	7	compound
9	because	SCONJ	13	mark
10	the	DET	11	det
11	price	NOUN	13	nsubj
12	was	AUX	13	cop
13	lower	ADJ	3	advcl
14	than	ADP	15	case
15	everyone	PRON	13	obl
16	else	ADJ	15	amod
17	,	PUNCT	19	punct
18	i	PRON	19	nsubj
19	got	VERB	3	parataxis
20	my	PRON	21	nmod:poss
21	computer	NOUN	19	obj
22	back	ADV	19	advmod
23	the	DET	25	det
24	next	ADJ	25	amod
25	day	NOUN	19	obl:tmod
26	,	PUNCT	33	punct
27	and	CCONJ	33	cc
28	the	DET	29	det
29	professionalism	NOUN	33	nsubj
30	he	PRON	31	nsubj
31	showed	VERB	29	acl:relcl
32	was	AUX	33	cop
33	great	ADJ	3	conj
34	.	PUNCT	3	punct