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 noticia del hallazgo de la nieta de Gelman ha provocado una auténtica conmoción en Uruguay, ya que es la primera vez que un presidente asume el problema de los desaparecidos.
Postion	Tokenization
1	La
2	noticia
3	del
4	hallazgo
5	de
6	la
7	nieta
8	de
9	Gelman
10	ha
11	provocado
12	una
13	auténtica
14	conmoción
15	en
16	Uruguay
17	,
18	ya
19	que
20	es
21	la
22	primera
23	vez
24	que
25	un
26	presidente
27	asume
28	el
29	problema
30	de
31	los
32	desaparecidos
33	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	noticia	NOUN	11	nsubj
3	del	ADP	4	case
4	hallazgo	NOUN	2	nmod
5	de	ADP	7	case
6	la	DET	7	det
7	nieta	NOUN	4	nmod
8	de	ADP	9	case
9	Gelman	PROPN	7	nmod
10	ha	AUX	11	aux
11	provocado	VERB	0	root
12	una	DET	14	det
13	auténtica	ADJ	14	amod
14	conmoción	NOUN	11	obj
15	en	ADP	16	case
16	Uruguay	PROPN	11	obl
17	,	PUNCT	23	punct
18	ya	ADV	23	mark
19	que	SCONJ	18	fixed
20	es	AUX	23	cop
21	la	DET	23	det
22	primera	ADJ	23	amod
23	vez	NOUN	11	advcl
24	que	PRON	27	obl
25	un	DET	26	det
26	presidente	NOUN	27	nsubj
27	asume	VERB	23	acl
28	el	DET	29	det
29	problema	NOUN	27	obj
30	de	ADP	32	case
31	los	DET	32	det
32	desaparecidos	ADJ	29	amod
33	.	PUNCT	11	punct