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 portavoz del PSOE, Bernardo Bueno, dijo que "la amenaza ya no es fantasma ni virtual, sino real, el Gobierno del PP ha fijado la libertad de descuentos en la venta de los precios de los libros", medida que calificó de "error", tras asegurar que "ha fracasado en otros países", donde se han visto perjudicadas las pequeñas librerías y los propios consumidores porque, "al final, el precio no ha bajado".
Postion	Tokenization
1	El
2	portavoz
3	del
4	PSOE
5	,
6	Bernardo
7	Bueno
8	,
9	dijo
10	que
11	"
12	la
13	amenaza
14	ya
15	no
16	es
17	fantasma
18	ni
19	virtual
20	,
21	sino
22	real
23	,
24	el
25	Gobierno
26	del
27	PP
28	ha
29	fijado
30	la
31	libertad
32	de
33	descuentos
34	en
35	la
36	venta
37	de
38	los
39	precios
40	de
41	los
42	libros
43	"
44	,
45	medida
46	que
47	calificó
48	de
49	"
50	error
51	"
52	,
53	tras
54	asegurar
55	que
56	"
57	ha
58	fracasado
59	en
60	otros
61	países
62	"
63	,
64	donde
65	se
66	han
67	visto
68	perjudicadas
69	las
70	pequeñas
71	librerías
72	y
73	los
74	propios
75	consumidores
76	porque
77	,
78	"
79	al
80	final
81	,
82	el
83	precio
84	no
85	ha
86	bajado
87	"
88	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	portavoz	NOUN	9	nsubj
3	del	ADP	4	case
4	PSOE	PROPN	2	nmod
5	,	PUNCT	6	punct
6	Bernardo	PROPN	2	appos
7	Bueno	PROPN	6	flat
8	,	PUNCT	6	punct
9	dijo	VERB	0	root
10	que	SCONJ	17	mark
11	"	PUNCT	17	punct
12	la	DET	13	det
13	amenaza	NOUN	17	nsubj
14	ya	ADV	17	advmod
15	no	ADV	17	advmod
16	es	AUX	17	cop
17	fantasma	ADJ	9	ccomp
18	ni	CCONJ	19	cc
19	virtual	ADJ	17	conj
20	,	PUNCT	17	punct
21	sino	CCONJ	17	cc
22	real	ADJ	17	advmod
23	,	PUNCT	17	punct
24	el	DET	25	det
25	Gobierno	PROPN	29	nsubj
26	del	ADP	27	case
27	PP	PROPN	25	nmod
28	ha	AUX	29	aux
29	fijado	VERB	17	advcl
30	la	DET	31	det
31	libertad	NOUN	29	obj
32	de	ADP	33	case
33	descuentos	NOUN	31	nmod
34	en	ADP	36	case
35	la	DET	36	det
36	venta	NOUN	33	nmod
37	de	ADP	39	case
38	los	DET	39	det
39	precios	NOUN	36	nmod
40	de	ADP	42	case
41	los	DET	42	det
42	libros	NOUN	39	nmod
43	"	PUNCT	45	punct
44	,	PUNCT	45	punct
45	medida	NOUN	31	appos
46	que	PRON	47	obj
47	calificó	VERB	45	acl
48	de	ADP	50	case
49	"	PUNCT	50	punct
50	error	NOUN	47	obj
51	"	PUNCT	50	punct
52	,	PUNCT	54	punct
53	tras	ADP	54	mark
54	asegurar	VERB	47	advcl
55	que	SCONJ	54	mark
56	"	PUNCT	54	punct
57	ha	AUX	54	aux
58	fracasado	VERB	54	xcomp
59	en	ADP	61	case
60	otros	DET	61	det
61	países	NOUN	54	obl
62	"	PUNCT	67	punct
63	,	PUNCT	67	punct
64	donde	PRON	67	obl
65	se	PRON	67	expl:pv
66	han	AUX	67	aux
67	visto	VERB	61	acl
68	perjudicadas	ADJ	67	obj
69	las	DET	71	det
70	pequeñas	ADJ	71	amod
71	librerías	NOUN	67	nsubj
72	y	CCONJ	75	cc
73	los	DET	75	det
74	propios	DET	73	det
75	consumidores	NOUN	71	conj
76	porque	SCONJ	86	mark
77	,	PUNCT	79	punct
78	"	PUNCT	79	punct
79	al	ADP	86	advmod
80	final	NOUN	79	fixed
81	,	PUNCT	79	punct
82	el	DET	83	det
83	precio	NOUN	86	nsubj
84	no	ADV	86	advmod
85	ha	AUX	86	aux
86	bajado	VERB	67	advcl
87	"	PUNCT	17	punct
88	.	PUNCT	9	punct