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:
El ajuste laboral afectará especialmente a Francia, donde se concentrarán 1.500 despidos, mientras que en España sólo están previstas 20 rescisiones de contratos.
Postion	Tokenization
1	El
2	ajuste
3	laboral
4	afectará
5	especialmente
6	a
7	Francia
8	,
9	donde
10	se
11	concentrarán
12	1.500
13	despidos
14	,
15	mientras
16	que
17	en
18	España
19	sólo
20	están
21	previstas
22	20
23	rescisiones
24	de
25	contratos
26	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	ajuste	NOUN	4	nsubj
3	laboral	ADJ	2	amod
4	afectará	VERB	15	parataxis
5	especialmente	ADV	4	obj
6	a	ADP	5	case
7	Francia	PROPN	5	nmod
8	,	PUNCT	11	punct
9	donde	PRON	11	obl
10	se	PRON	11	expl:pv
11	concentrarán	VERB	7	acl
12	1.500	NUM	13	nummod
13	despidos	NOUN	11	nsubj
14	,	PUNCT	15	punct
15	mientras	CCONJ	0	root
16	que	SCONJ	15	fixed
17	en	ADP	18	case
18	España	PROPN	21	obl
19	sólo	ADV	21	advmod
20	están	AUX	21	cop
21	previstas	ADJ	15	parataxis
22	20	NUM	23	nummod
23	rescisiones	NOUN	21	nsubj
24	de	ADP	25	case
25	contratos	NOUN	23	nmod
26	.	PUNCT	15	punct