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:
Ante unas mil personas, entre ellas la ministra de Ciencia y Tecnología, Anna Birulés, el alcalde de Barcelona, Joan Clos, la Delegada del Gobierno, Julia García Valdecasas, y una nutrida representación del gobierno catalán, Pujol dio un toque de alerta sobre el aumento de los accidentes laborales.
Postion	Tokenization
1	Ante
2	unas
3	mil
4	personas
5	,
6	entre
7	ellas
8	la
9	ministra
10	de
11	Ciencia
12	y
13	Tecnología
14	,
15	Anna
16	Birulés
17	,
18	el
19	alcalde
20	de
21	Barcelona
22	,
23	Joan
24	Clos
25	,
26	la
27	Delegada
28	del
29	Gobierno
30	,
31	Julia
32	García
33	Valdecasas
34	,
35	y
36	una
37	nutrida
38	representación
39	del
40	gobierno
41	catalán
42	,
43	Pujol
44	dio
45	un
46	toque
47	de
48	alerta
49	sobre
50	el
51	aumento
52	de
53	los
54	accidentes
55	laborales
56	.
Position	Tokenization	UPOS	Head	Deprel
1	Ante	ADP	4	case
2	unas	DET	4	det
3	mil	NUM	2	nummod
4	personas	NOUN	44	obl
5	,	PUNCT	9	punct
6	entre	ADP	7	case
7	ellas	PRON	9	nmod
8	la	DET	9	det
9	ministra	NOUN	4	appos
10	de	ADP	11	case
11	Ciencia	PROPN	9	nmod
12	y	CCONJ	13	cc
13	Tecnología	PROPN	11	conj
14	,	PUNCT	15	punct
15	Anna	PROPN	9	appos
16	Birulés	PROPN	15	flat
17	,	PUNCT	19	punct
18	el	DET	19	det
19	alcalde	NOUN	9	appos
20	de	ADP	21	case
21	Barcelona	PROPN	19	nmod
22	,	PUNCT	23	punct
23	Joan	PROPN	19	appos
24	Clos	PROPN	23	flat
25	,	PUNCT	27	punct
26	la	DET	27	det
27	Delegada	PROPN	9	appos
28	del	ADP	29	case
29	Gobierno	PROPN	27	nmod
30	,	PUNCT	31	punct
31	Julia	PROPN	27	flat
32	García	PROPN	31	flat
33	Valdecasas	PROPN	31	flat
34	,	PUNCT	31	punct
35	y	CCONJ	38	cc
36	una	DET	38	det
37	nutrida	ADJ	38	amod
38	representación	NOUN	9	conj
39	del	ADP	40	case
40	gobierno	NOUN	38	nmod
41	catalán	ADJ	40	amod
42	,	PUNCT	9	punct
43	Pujol	PROPN	44	nsubj
44	dio	VERB	0	root
45	un	DET	46	det
46	toque	NOUN	44	obj
47	de	ADP	48	case
48	alerta	NOUN	46	nmod
49	sobre	ADP	51	case
50	el	DET	51	det
51	aumento	NOUN	44	obl
52	de	ADP	54	case
53	los	DET	54	det
54	accidentes	NOUN	51	nmod
55	laborales	ADJ	54	amod
56	.	PUNCT	44	punct