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:
En los países con los mejores sistemas de I+D, explicó, la industria es la responsable de un 60% de la investigación, pero en España no llega ni a la mitad.
Postion	Tokenization
1	En
2	los
3	países
4	con
5	los
6	mejores
7	sistemas
8	de
9	I+D
10	,
11	explicó
12	,
13	la
14	industria
15	es
16	la
17	responsable
18	de
19	un
20	60%
21	de
22	la
23	investigación
24	,
25	pero
26	en
27	España
28	no
29	llega
30	ni
31	a
32	la
33	mitad
34	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	3	case
2	los	DET	3	det
3	países	NOUN	17	obl
4	con	ADP	7	case
5	los	DET	7	det
6	mejores	ADJ	7	amod
7	sistemas	NOUN	3	nmod
8	de	ADP	9	case
9	I+D	PROPN	7	nmod
10	,	PUNCT	11	punct
11	explicó	VERB	17	parataxis
12	,	PUNCT	11	punct
13	la	DET	14	det
14	industria	NOUN	17	nsubj
15	es	AUX	17	cop
16	la	DET	17	det
17	responsable	ADJ	0	root
18	de	ADP	20	case
19	un	DET	20	det
20	60%	SYM	17	nmod
21	de	ADP	23	case
22	la	DET	23	det
23	investigación	NOUN	20	nmod
24	,	PUNCT	29	punct
25	pero	CCONJ	29	cc
26	en	ADP	27	case
27	España	PROPN	29	obl
28	no	ADV	29	advmod
29	llega	VERB	17	conj
30	ni	ADV	29	obj
31	a	ADP	30	case
32	la	DET	33	det
33	mitad	NOUN	30	nmod
34	.	PUNCT	17	punct