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:
Insuficiente fue el crecimiento del PSOE en la Comunidad de Madrid, que obtuvo 12 escaños, uno más que en las generales de hace cuatro años, pese a perder casi 30.000 votos y quedarse con algo más 1.008.000 y que no sirvió para frenar la derrota global.
Postion	Tokenization
1	Insuficiente
2	fue
3	el
4	crecimiento
5	del
6	PSOE
7	en
8	la
9	Comunidad
10	de
11	Madrid
12	,
13	que
14	obtuvo
15	12
16	escaños
17	,
18	uno
19	más
20	que
21	en
22	las
23	generales
24	de
25	hace
26	cuatro
27	años
28	,
29	pese
30	a
31	perder
32	casi
33	30.000
34	votos
35	y
36	quedarse
37	quedar
38	se
39	con
40	algo
41	más
42	1.008.000
43	y
44	que
45	no
46	sirvió
47	para
48	frenar
49	la
50	derrota
51	global
52	.
Position	Tokenization	UPOS	Head	Deprel
1	Insuficiente	ADJ	0	root
2	fue	AUX	1	cop
3	el	DET	4	det
4	crecimiento	NOUN	1	nsubj
5	del	ADP	6	case
6	PSOE	PROPN	4	nmod
7	en	ADP	9	case
8	la	DET	9	det
9	Comunidad	PROPN	1	obl
10	de	ADP	11	case
11	Madrid	PROPN	9	flat
12	,	PUNCT	14	punct
13	que	PRON	14	nsubj
14	obtuvo	VERB	1	advcl
15	12	NUM	16	nummod
16	escaños	NOUN	14	obj
17	,	PUNCT	18	punct
18	uno	PRON	16	appos
19	más	ADV	18	advmod
20	que	SCONJ	23	mark
21	en	ADP	23	case
22	las	DET	23	det
23	generales	NOUN	18	nmod
24	de	ADP	25	mark
25	hace	VERB	23	advcl
26	cuatro	NUM	27	nummod
27	años	NOUN	25	obj
28	,	PUNCT	31	punct
29	pese	NOUN	31	mark
30	a	ADP	29	fixed
31	perder	VERB	14	advcl
32	casi	ADV	34	advmod
33	30.000	NUM	32	nummod
34	votos	NOUN	31	obj
35	y	CCONJ	36	cc
36	quedarse	_	None	_
37	quedar	VERB	31	conj
38	se	PRON	36	expl:pv
39	con	ADP	41	case
40	algo	ADV	41	advmod
41	más	ADV	39	advmod
42	1.008.000	NUM	36	obj
43	y	CCONJ	45	cc
44	que	PRON	45	nsubj
45	no	ADV	45	advmod
46	sirvió	VERB	1	advcl
47	para	ADP	47	mark
48	frenar	VERB	45	xcomp
49	la	DET	49	det
50	derrota	NOUN	47	obj
51	global	ADJ	49	amod
52	.	PUNCT	1	punct