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:
Recordó que Andalucía tiene el tercer sector editorial del país y que en esta comunidad se editan incluso libros en euskera, por lo que la liberalización afectará negativamente al mercado editorial andaluz.
Postion	Tokenization
1	Recordó
2	que
3	Andalucía
4	tiene
5	el
6	tercer
7	sector
8	editorial
9	del
10	país
11	y
12	que
13	en
14	esta
15	comunidad
16	se
17	editan
18	incluso
19	libros
20	en
21	euskera
22	,
23	por
24	lo
25	que
26	la
27	liberalización
28	afectará
29	negativamente
30	al
31	mercado
32	editorial
33	andaluz
34	.
Position	Tokenization	UPOS	Head	Deprel
1	Recordó	VERB	0	root
2	que	SCONJ	4	mark
3	Andalucía	PROPN	4	nsubj
4	tiene	VERB	1	ccomp
5	el	DET	7	det
6	tercer	ADJ	7	amod
7	sector	NOUN	4	obj
8	editorial	ADJ	7	amod
9	del	ADP	10	case
10	país	NOUN	7	nmod
11	y	CCONJ	17	cc
12	que	SCONJ	17	mark
13	en	ADP	15	case
14	esta	DET	15	det
15	comunidad	NOUN	17	obl
16	se	PRON	17	expl:pass
17	editan	VERB	4	conj
18	incluso	ADV	17	advmod
19	libros	NOUN	17	nsubj
20	en	ADP	21	case
21	euskera	NOUN	19	nmod
22	,	PUNCT	28	punct
23	por	ADP	28	mark
24	lo	PRON	28	det
25	que	PRON	28	obl
26	la	DET	27	det
27	liberalización	NOUN	28	nsubj
28	afectará	VERB	1	advcl
29	negativamente	ADV	28	advmod
30	al	ADP	31	case
31	mercado	NOUN	28	obj
32	editorial	ADJ	31	amod
33	andaluz	ADJ	31	amod
34	.	PUNCT	1	punct