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:
El presidente del Gobierno mostró su confianza en conseguir, durante la próxima legislatura, otros 1,8 millones de empleos, además de sacar adelante otros proyectos como la aprobación de la Ley de Humanidades o la modificación de la Ley de Extranjería, cuyo paso por las Cortes ha demostrado, según dijo, que "algunos prefieren perjudicar a su país" por "el placer" de que el Gobierno "no tenga una victoria parlamentaria".
Postion	Tokenization
1	El
2	presidente
3	del
4	Gobierno
5	mostró
6	su
7	confianza
8	en
9	conseguir
10	,
11	durante
12	la
13	próxima
14	legislatura
15	,
16	otros
17	1,8
18	millones
19	de
20	empleos
21	,
22	además
23	de
24	sacar
25	adelante
26	otros
27	proyectos
28	como
29	la
30	aprobación
31	de
32	la
33	Ley
34	de
35	Humanidades
36	o
37	la
38	modificación
39	de
40	la
41	Ley
42	de
43	Extranjería
44	,
45	cuyo
46	paso
47	por
48	las
49	Cortes
50	ha
51	demostrado
52	,
53	según
54	dijo
55	,
56	que
57	"
58	algunos
59	prefieren
60	perjudicar
61	a
62	su
63	país
64	"
65	por
66	"
67	el
68	placer
69	"
70	de
71	que
72	el
73	Gobierno
74	"
75	no
76	tenga
77	una
78	victoria
79	parlamentaria
80	"
81	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	presidente	NOUN	5	nsubj
3	del	ADP	4	case
4	Gobierno	PROPN	2	nmod
5	mostró	VERB	0	root
6	su	DET	7	det
7	confianza	NOUN	5	obj
8	en	ADP	7	mark
9	conseguir	VERB	8	conj
10	,	PUNCT	14	punct
11	durante	ADP	14	case
12	la	DET	14	det
13	próxima	ADJ	14	amod
14	legislatura	NOUN	9	obl
15	,	PUNCT	14	punct
16	otros	PRON	18	nmod
17	1,8	NUM	16	nummod
18	millones	NOUN	9	obj
19	de	ADP	20	case
20	empleos	NOUN	18	nmod
21	,	PUNCT	24	punct
22	además	ADV	24	cc
23	de	ADP	22	fixed
24	sacar	VERB	8	conj
25	adelante	ADV	24	advmod
26	otros	DET	27	det
27	proyectos	NOUN	24	obj
28	como	SCONJ	30	mark
29	la	DET	30	det
30	aprobación	NOUN	27	nmod
31	de	ADP	33	case
32	la	DET	33	det
33	Ley	PROPN	30	nmod
34	de	ADP	35	case
35	Humanidades	PROPN	33	flat
36	o	CCONJ	38	cc
37	la	DET	38	det
38	modificación	NOUN	30	conj
39	de	ADP	41	case
40	la	DET	41	det
41	Ley	PROPN	38	nmod
42	de	ADP	43	case
43	Extranjería	PROPN	41	flat
44	,	PUNCT	51	punct
45	cuyo	PRON	46	nmod
46	paso	NOUN	51	nsubj
47	por	ADP	49	case
48	las	DET	49	det
49	Cortes	PROPN	46	nmod
50	ha	AUX	51	aux
51	demostrado	VERB	41	acl
52	,	PUNCT	54	punct
53	según	SCONJ	54	mark
54	dijo	VERB	51	advcl
55	,	PUNCT	54	punct
56	que	SCONJ	59	mark
57	"	PUNCT	59	punct
58	algunos	PRON	59	nsubj
59	prefieren	VERB	51	ccomp
60	perjudicar	VERB	59	xcomp
61	a	ADP	63	case
62	su	DET	63	det
63	país	NOUN	60	obj
64	"	PUNCT	59	punct
65	por	ADP	68	case
66	"	PUNCT	68	punct
67	el	DET	68	det
68	placer	NOUN	59	obl
69	"	PUNCT	68	punct
70	de	ADP	76	mark
71	que	SCONJ	76	mark
72	el	DET	73	det
73	Gobierno	PROPN	76	nsubj
74	"	PUNCT	76	punct
75	no	ADV	76	advmod
76	tenga	VERB	68	acl
77	una	DET	78	det
78	victoria	NOUN	76	obj
79	parlamentaria	ADJ	78	amod
80	"	PUNCT	76	punct
81	.	PUNCT	5	punct