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've read some of the reviews below and would like to state that yes, like any other doctors office there is sometimes a wait (depending on what other patients are being seen for) and some of the tests and procedures that are ran can be costly (just like they would be for any other medical tests elsewhere if you do not have insurance)...
Postion	Tokenization
1	I've
2	I
3	've
4	read
5	some
6	of
7	the
8	reviews
9	below
10	and
11	would
12	like
13	to
14	state
15	that
16	yes
17	,
18	like
19	any
20	other
21	doctors
22	doctor
23	s
24	office
25	there
26	is
27	sometimes
28	a
29	wait
30	(
31	depending
32	on
33	what
34	other
35	patients
36	are
37	being
38	seen
39	for
40	)
41	and
42	some
43	of
44	the
45	tests
46	and
47	procedures
48	that
49	are
50	ran
51	can
52	be
53	costly
54	(
55	just
56	like
57	they
58	would
59	be
60	for
61	any
62	other
63	medical
64	tests
65	elsewhere
66	if
67	you
68	do
69	not
70	have
71	insurance
72	)
73	...
Position	Tokenization	UPOS	Head	Deprel
1	I've	_	None	_
2	I	PRON	3	nsubj
3	've	AUX	3	aux
4	read	VERB	0	root
5	some	DET	3	obj
6	of	ADP	7	case
7	the	DET	7	det
8	reviews	NOUN	4	nmod
9	below	ADV	7	advmod
10	and	CCONJ	11	cc
11	would	AUX	11	aux
12	like	VERB	3	conj
13	to	PART	13	mark
14	state	VERB	11	xcomp
15	that	SCONJ	24	mark
16	yes	INTJ	24	discourse
17	,	PUNCT	24	punct
18	like	ADP	22	case
19	any	DET	22	det
20	other	ADJ	22	amod
21	doctors	_	None	_
22	doctor	NOUN	22	nmod:poss
23	s	PART	20	case
24	office	NOUN	24	obl
25	there	PRON	24	expl
26	is	VERB	13	ccomp
27	sometimes	ADV	24	advmod
28	a	DET	27	det
29	wait	NOUN	24	nsubj
30	(	PUNCT	31	punct
31	depending	VERB	31	case
32	on	SCONJ	31	case
33	what	PRON	24	obl
34	other	ADJ	33	amod
35	patients	NOUN	36	nsubj:pass
36	are	AUX	36	aux
37	being	AUX	36	aux:pass
38	seen	VERB	31	acl:relcl
39	for	ADP	36	obl
40	)	PUNCT	31	punct
41	and	CCONJ	51	cc
42	some	DET	51	nsubj
43	of	ADP	43	case
44	the	DET	43	det
45	tests	NOUN	40	nmod
46	and	CCONJ	45	cc
47	procedures	NOUN	43	conj
48	that	PRON	48	nsubj:pass
49	are	AUX	48	aux:pass
50	ran	VERB	43	acl:relcl
51	can	AUX	51	aux
52	be	AUX	51	cop
53	costly	ADJ	24	conj
54	(	PUNCT	57	punct
55	just	ADV	57	advmod
56	like	SCONJ	57	mark
57	they	PRON	57	nsubj
58	would	AUX	57	aux
59	be	VERB	51	parataxis
60	for	ADP	62	case
61	any	DET	62	det
62	other	ADJ	62	amod
63	medical	ADJ	62	amod
64	tests	NOUN	57	obl
65	elsewhere	ADV	57	advmod
66	if	SCONJ	68	mark
67	you	PRON	68	nsubj
68	do	AUX	68	aux
69	not	PART	68	advmod
70	have	VERB	57	advcl
71	insurance	NOUN	68	obj
72	)	PUNCT	57	punct
73	...	PUNCT	3	punct