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:
"Habrá que elegir entre el proyecto que ha creado en España 1,8 millones de puestos de trabajo en cuatro años y ha reducido la tasa de paro a la más baja en los últimos veinte años", y otros que "sólo son capaces de generar paro o retroceso", dijo Aznar.
Postion	Tokenization
1	"
2	Habrá
3	que
4	elegir
5	entre
6	el
7	proyecto
8	que
9	ha
10	creado
11	en
12	España
13	1,8
14	millones
15	de
16	puestos
17	de
18	trabajo
19	en
20	cuatro
21	años
22	y
23	ha
24	reducido
25	la
26	tasa
27	de
28	paro
29	a
30	la
31	más
32	baja
33	en
34	los
35	últimos
36	veinte
37	años
38	"
39	,
40	y
41	otros
42	que
43	"
44	sólo
45	son
46	capaces
47	de
48	generar
49	paro
50	o
51	retroceso
52	"
53	,
54	dijo
55	Aznar
56	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	2	punct
2	Habrá	AUX	54	ccomp
3	que	SCONJ	4	cc
4	elegir	VERB	2	conj
5	entre	ADP	7	case
6	el	DET	7	det
7	proyecto	NOUN	4	obl
8	que	PRON	10	nsubj
9	ha	AUX	10	aux
10	creado	VERB	7	acl
11	en	ADP	12	case
12	España	PROPN	10	obl
13	1,8	NUM	14	nummod
14	millones	NOUN	10	obj
15	de	ADP	16	case
16	puestos	NOUN	14	nmod
17	de	ADP	18	case
18	trabajo	NOUN	16	nmod
19	en	ADP	21	case
20	cuatro	NUM	21	nummod
21	años	NOUN	10	obl
22	y	CCONJ	24	cc
23	ha	AUX	24	aux
24	reducido	VERB	10	conj
25	la	DET	26	det
26	tasa	NOUN	24	obj
27	de	ADP	28	case
28	paro	NOUN	26	nmod
29	a	ADP	32	case
30	la	DET	32	det
31	más	ADV	32	advmod
32	baja	ADJ	24	advmod
33	en	ADP	37	case
34	los	DET	37	det
35	últimos	ADJ	34	amod
36	veinte	NUM	34	nummod
37	años	NOUN	32	nmod
38	"	PUNCT	41	punct
39	,	PUNCT	41	punct
40	y	CCONJ	41	cc
41	otros	PRON	7	conj
42	que	PRON	46	nsubj
43	"	PUNCT	46	punct
44	sólo	ADV	46	advmod
45	son	AUX	46	cop
46	capaces	ADJ	41	acl
47	de	ADP	48	mark
48	generar	VERB	46	acl
49	paro	NOUN	48	obj
50	o	CCONJ	51	cc
51	retroceso	NOUN	49	conj
52	"	PUNCT	2	punct
53	,	PUNCT	2	punct
54	dijo	VERB	0	root
55	Aznar	PROPN	54	nsubj
56	.	PUNCT	54	punct