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:
Miles de ciudadanos se manifestaron ayer en toda España para condenar el asesinato, a manos de ETA, del ex gobernador civil de Guipúzcoa Juan María Jáuregui.
Postion	Tokenization
1	Miles
2	de
3	ciudadanos
4	se
5	manifestaron
6	ayer
7	en
8	toda
9	España
10	para
11	condenar
12	el
13	asesinato
14	,
15	a
16	manos
17	de
18	ETA
19	,
20	del
21	ex
22	gobernador
23	civil
24	de
25	Guipúzcoa
26	Juan
27	María
28	Jáuregui
29	.
Position	Tokenization	UPOS	Head	Deprel
1	Miles	NUM	5	nsubj
2	de	ADP	3	case
3	ciudadanos	NOUN	1	nmod
4	se	PRON	5	expl:pv
5	manifestaron	VERB	0	root
6	ayer	ADV	5	advmod
7	en	ADP	9	case
8	toda	DET	9	det
9	España	PROPN	5	obl
10	para	ADP	11	mark
11	condenar	VERB	5	advcl
12	el	DET	13	det
13	asesinato	NOUN	11	obj
14	,	PUNCT	16	punct
15	a	ADP	16	case
16	manos	NOUN	13	nmod
17	de	ADP	18	case
18	ETA	PROPN	16	nmod
19	,	PUNCT	16	punct
20	del	ADP	22	case
21	ex	ADJ	22	amod
22	gobernador	NOUN	13	nmod
23	civil	ADJ	22	amod
24	de	ADP	25	case
25	Guipúzcoa	PROPN	22	nmod
26	Juan	PROPN	22	appos
27	María	PROPN	26	flat
28	Jáuregui	PROPN	26	flat
29	.	PUNCT	5	punct