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:
prepared the road test with a driving ... prepared the road test with a driving school in edmonton, but my instructor only trained me in a narrow street, hence I took one 90 minute lesson from the Noble driving school to learn the skill of changing lane, and found them very friendly and professional.
Postion	Tokenization
1	prepared
2	the
3	road
4	test
5	with
6	a
7	driving
8	...
9	prepared
10	the
11	road
12	test
13	with
14	a
15	driving
16	school
17	in
18	edmonton
19	,
20	but
21	my
22	instructor
23	only
24	trained
25	me
26	in
27	a
28	narrow
29	street
30	,
31	hence
32	I
33	took
34	one
35	90
36	minute
37	lesson
38	from
39	the
40	Noble
41	driving
42	school
43	to
44	learn
45	the
46	skill
47	of
48	changing
49	lane
50	,
51	and
52	found
53	them
54	very
55	friendly
56	and
57	professional
58	.
Position	Tokenization	UPOS	Head	Deprel
1	prepared	VERB	0	root
2	the	DET	4	det
3	road	NOUN	4	compound
4	test	NOUN	1	obj
5	with	ADP	7	case
6	a	DET	7	det
7	driving	NOUN	1	obl
8	...	PUNCT	1	punct
9	prepared	VERB	1	parataxis
10	the	DET	12	det
11	road	NOUN	12	compound
12	test	NOUN	9	obj
13	with	ADP	16	case
14	a	DET	16	det
15	driving	NOUN	16	compound
16	school	NOUN	9	obl
17	in	ADP	18	case
18	edmonton	PROPN	16	nmod
19	,	PUNCT	24	punct
20	but	CCONJ	24	cc
21	my	PRON	22	nmod:poss
22	instructor	NOUN	24	nsubj
23	only	ADV	24	advmod
24	trained	VERB	1	conj
25	me	PRON	24	obj
26	in	ADP	29	case
27	a	DET	29	det
28	narrow	ADJ	29	amod
29	street	NOUN	24	obl
30	,	PUNCT	33	punct
31	hence	ADV	33	advmod
32	I	PRON	33	nsubj
33	took	VERB	1	conj
34	one	NUM	37	nummod
35	90	NUM	36	nummod
36	minute	NOUN	37	compound
37	lesson	NOUN	33	obj
38	from	ADP	42	case
39	the	DET	42	det
40	Noble	PROPN	42	compound
41	driving	PROPN	42	compound
42	school	PROPN	37	nmod
43	to	PART	44	mark
44	learn	VERB	33	advcl
45	the	DET	46	det
46	skill	NOUN	44	obj
47	of	SCONJ	48	mark
48	changing	VERB	46	acl
49	lane	NOUN	48	obj
50	,	PUNCT	52	punct
51	and	CCONJ	52	cc
52	found	VERB	33	conj
53	them	PRON	52	obj
54	very	ADV	55	advmod
55	friendly	ADJ	52	xcomp
56	and	CCONJ	57	cc
57	professional	ADJ	55	conj
58	.	PUNCT	1	punct