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 profesor Barron Lerner describe cómo la mítica Evita, que fue primera dama argentina, ignoraba que su histerectomía por cáncer cervical fue realizada en secreto por un oncólogo estadounidense, el doctor George Pack.
Postion	Tokenization
1	El
2	profesor
3	Barron
4	Lerner
5	describe
6	cómo
7	la
8	mítica
9	Evita
10	,
11	que
12	fue
13	primera
14	dama
15	argentina
16	,
17	ignoraba
18	que
19	su
20	histerectomía
21	por
22	cáncer
23	cervical
24	fue
25	realizada
26	en
27	secreto
28	por
29	un
30	oncólogo
31	estadounidense
32	,
33	el
34	doctor
35	George
36	Pack
37	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	profesor	NOUN	5	nsubj
3	Barron	PROPN	2	appos
4	Lerner	PROPN	3	flat
5	describe	VERB	0	root
6	cómo	PRON	17	obl
7	la	DET	9	det
8	mítica	ADJ	9	amod
9	Evita	PROPN	17	nsubj
10	,	PUNCT	14	punct
11	que	PRON	14	nsubj
12	fue	AUX	14	cop
13	primera	ADJ	14	amod
14	dama	NOUN	9	acl
15	argentina	ADJ	14	amod
16	,	PUNCT	14	punct
17	ignoraba	VERB	5	ccomp
18	que	SCONJ	25	mark
19	su	DET	20	det
20	histerectomía	NOUN	25	nsubj
21	por	ADP	22	case
22	cáncer	NOUN	20	nmod
23	cervical	ADJ	22	amod
24	fue	AUX	25	aux
25	realizada	VERB	17	ccomp
26	en	ADP	25	advmod
27	secreto	NOUN	26	fixed
28	por	ADP	30	case
29	un	DET	30	det
30	oncólogo	NOUN	25	obj
31	estadounidense	ADJ	30	amod
32	,	PUNCT	34	punct
33	el	DET	34	det
34	doctor	NOUN	30	appos
35	George	PROPN	34	appos
36	Pack	PROPN	35	flat
37	.	PUNCT	5	punct