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 text: This is unlike the situation last year in Asia when we evacuated U.S. citizens from areas that were hit by the tsunami - a phenomenon that is much less predictable than the Hezbollah-provoked destruction that rained down on Lebanon.
Position	Tokenization	UPOS	Head	Deprel
1	This	PRON	5	nsubj
2	is	AUX	5	cop
3	unlike	ADP	5	case
4	the	DET	5	det
5	situation	NOUN	0	root
6	last	ADJ	7	amod
7	year	NOUN	5	obl:tmod
8	in	ADP	9	case
9	Asia	PROPN	5	nmod
10	when	SCONJ	12	mark
11	we	PRON	12	nsubj
12	evacuated	VERB	5	acl:relcl
13	U.S.	PROPN	14	compound
14	citizens	NOUN	12	obj
15	from	ADP	16	case
16	areas	NOUN	12	obl
17	that	PRON	19	nsubj:pass
18	were	AUX	19	aux:pass
19	hit	VERB	16	acl:relcl
20	by	ADP	22	case
21	the	DET	22	det
22	tsunami	NOUN	19	obl
23	-	PUNCT	22	punct
24	a	DET	25	det
25	phenomenon	NOUN	22	appos
26	that	PRON	30	nsubj
27	is	AUX	30	cop
28	much	ADV	29	advmod
29	less	ADV	30	advmod
30	predictable	ADJ	25	acl:relcl
31	than	ADP	36	case
32	the	DET	36	det
33	Hezbollah	PROPN	35	compound
34	-	PUNCT	35	punct
35	provoked	VERB	36	amod
36	destruction	NOUN	30	obl
37	that	PRON	38	nsubj
38	rained	VERB	36	acl:relcl
39	down	ADV	38	advmod
40	on	ADP	41	case
41	Lebanon	PROPN	38	obl
42	.	PUNCT	5	punct