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:
She had to hack her way through the ceiling of her beauty shop as flood waters rose in the city of half a million people - much of which lies below sea level.
Postion	Tokenization
1	She
2	had
3	to
4	hack
5	her
6	way
7	through
8	the
9	ceiling
10	of
11	her
12	beauty
13	shop
14	as
15	flood
16	waters
17	rose
18	in
19	the
20	city
21	of
22	half
23	a
24	million
25	people
26	-
27	much
28	of
29	which
30	lies
31	below
32	sea
33	level
34	.
Position	Tokenization	UPOS	Head	Deprel
1	She	PRON	2	nsubj
2	had	VERB	0	root
3	to	PART	4	mark
4	hack	VERB	2	xcomp
5	her	PRON	6	nmod:poss
6	way	NOUN	4	obj
7	through	ADP	9	case
8	the	DET	9	det
9	ceiling	NOUN	4	obl
10	of	ADP	13	case
11	her	PRON	13	nmod:poss
12	beauty	NOUN	13	compound
13	shop	NOUN	9	nmod
14	as	SCONJ	17	mark
15	flood	NOUN	16	compound
16	waters	NOUN	17	nsubj
17	rose	VERB	4	advcl
18	in	ADP	20	case
19	the	DET	20	det
20	city	NOUN	17	obl
21	of	ADP	25	case
22	half	DET	24	compound
23	a	DET	24	det
24	million	NUM	25	nummod
25	people	NOUN	20	nmod
26	-	PUNCT	20	punct
27	much	ADJ	30	nsubj
28	of	ADP	29	case
29	which	PRON	27	obl
30	lies	VERB	20	acl:relcl
31	below	ADP	33	case
32	sea	NOUN	33	compound
33	level	NOUN	30	obl
34	.	PUNCT	2	punct