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:
La búsqueda de Gelman despertó una amplia solidaridad internacional tras la negativa del ex presidente uruguayo Sanguinetti a aportar datos al poeta sobre el paradero de su nieta.
Postion	Tokenization
1	La
2	búsqueda
3	de
4	Gelman
5	despertó
6	una
7	amplia
8	solidaridad
9	internacional
10	tras
11	la
12	negativa
13	del
14	ex
15	presidente
16	uruguayo
17	Sanguinetti
18	a
19	aportar
20	datos
21	al
22	poeta
23	sobre
24	el
25	paradero
26	de
27	su
28	nieta
29	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	búsqueda	NOUN	5	nsubj
3	de	ADP	4	case
4	Gelman	PROPN	2	nmod
5	despertó	VERB	0	root
6	una	DET	8	det
7	amplia	ADJ	8	amod
8	solidaridad	NOUN	5	obj
9	internacional	ADJ	8	amod
10	tras	ADP	12	case
11	la	DET	12	det
12	negativa	NOUN	5	obl
13	del	ADP	15	case
14	ex	ADJ	15	amod
15	presidente	NOUN	12	nmod
16	uruguayo	ADJ	15	amod
17	Sanguinetti	PROPN	15	appos
18	a	ADP	19	mark
19	aportar	VERB	12	acl
20	datos	NOUN	19	obj
21	al	ADP	22	case
22	poeta	NOUN	19	obj
23	sobre	ADP	25	case
24	el	DET	25	det
25	paradero	NOUN	19	obl
26	de	ADP	28	case
27	su	DET	28	det
28	nieta	NOUN	25	nmod
29	.	PUNCT	5	punct