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:
Los industriales han calculado que, pese a la esperada reactivación, en los tres primeros meses del año 2000 se han perdido entre 2.600 y 2.700 puestos de trabajo en el sector manufacturero.
Postion	Tokenization
1	Los
2	industriales
3	han
4	calculado
5	que
6	,
7	pese
8	a
9	la
10	esperada
11	reactivación
12	,
13	en
14	los
15	tres
16	primeros
17	meses
18	del
19	año
20	2000
21	se
22	han
23	perdido
24	entre
25	2.600
26	y
27	2.700
28	puestos
29	de
30	trabajo
31	en
32	el
33	sector
34	manufacturero
35	.
Position	Tokenization	UPOS	Head	Deprel
1	Los	DET	2	det
2	industriales	NOUN	4	nsubj
3	han	AUX	4	aux
4	calculado	VERB	0	root
5	que	SCONJ	23	mark
6	,	PUNCT	11	punct
7	pese	NOUN	11	case
8	a	ADP	7	fixed
9	la	DET	11	det
10	esperada	ADJ	11	amod
11	reactivación	NOUN	23	obl
12	,	PUNCT	11	punct
13	en	ADP	17	case
14	los	DET	17	det
15	tres	NUM	14	nummod
16	primeros	ADJ	17	amod
17	meses	NOUN	23	obl
18	del	ADP	19	case
19	año	NOUN	17	nmod
20	2000	NUM	19	compound
21	se	PRON	23	expl:pass
22	han	AUX	23	aux
23	perdido	VERB	4	ccomp
24	entre	ADP	25	case
25	2.600	NUM	28	nummod
26	y	CCONJ	27	cc
27	2.700	NUM	25	conj
28	puestos	NOUN	23	nsubj
29	de	ADP	30	case
30	trabajo	NOUN	28	nmod
31	en	ADP	33	case
32	el	DET	33	det
33	sector	NOUN	23	obl
34	manufacturero	ADJ	33	amod
35	.	PUNCT	4	punct