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:
"No nos temblará la mano", afirmó el diputado, que es presidente del Centre d'Estudis Europeus per la Formació dels Treballadors (CEEFT), que también recibió centenares de millones en subvenciones de Treball.
Postion	Tokenization
1	"
2	No
3	nos
4	temblará
5	la
6	mano
7	"
8	,
9	afirmó
10	el
11	diputado
12	,
13	que
14	es
15	presidente
16	del
17	Centre
18	d'Estudis
19	Europeus
20	per
21	la
22	Formació
23	dels
24	Treballadors
25	(
26	CEEFT
27	)
28	,
29	que
30	también
31	recibió
32	centenares
33	de
34	millones
35	en
36	subvenciones
37	de
38	Treball
39	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	4	punct
2	No	ADV	4	advmod
3	nos	PRON	4	iobj
4	temblará	VERB	9	ccomp
5	la	DET	6	det
6	mano	NOUN	4	nsubj
7	"	PUNCT	4	punct
8	,	PUNCT	4	punct
9	afirmó	VERB	0	root
10	el	DET	11	det
11	diputado	NOUN	9	nsubj
12	,	PUNCT	15	punct
13	que	PRON	15	nsubj
14	es	AUX	15	cop
15	presidente	NOUN	11	acl
16	del	ADP	17	case
17	Centre	PROPN	15	nmod
18	d'Estudis	PROPN	17	flat
19	Europeus	PROPN	17	flat
20	per	ADP	22	case
21	la	DET	22	det
22	Formació	PROPN	17	flat
23	dels	ADP	24	case
24	Treballadors	PROPN	17	flat
25	(	PUNCT	26	punct
26	CEEFT	PROPN	17	flat
27	)	PUNCT	26	punct
28	,	PUNCT	15	punct
29	que	PRON	31	nsubj
30	también	ADV	31	advmod
31	recibió	VERB	15	advcl
32	centenares	NOUN	31	obj
33	de	ADP	34	case
34	millones	NOUN	32	nmod
35	en	ADP	36	case
36	subvenciones	NOUN	34	nmod
37	de	ADP	38	case
38	Treball	PROPN	36	nmod
39	.	PUNCT	9	punct