Thanks. I figured grammatical # as such would be discarded as unnecessary but the notion of plurality raises semantic issues that natural language sidesteps by ambiguity.

Disclaimer/Personal Background (trying to be brief): I've often been told I've got an unusual cognitive style (for lack of better term) and I've often felt very much as if there's an impedance mismatch between how my thoughts are structured and how language operates; in essence, at the word-or-sentence level everything I hear or read is very polyvalent and vague, and only take on a concrete meaning to me if I get multiple paraphrases of it...it's putting all the variants into superposition and seeing which parts reinforce or cancel shows me the contour of the actual meaning (which itself is not necessarily ever actually "represented in words" so much as "gets the outline of its semantic boundaries painted").

In the abstract this leaves me with an interest in the idea of something like lojban but very mixed initial reactions: it's possible an artificial language with more-precise meanings would eliminate my need for doing verbal interferometry across multiple paraphrases but on the other
hand I have a lifetime's experience feeling very uncomfortable without tons of redundancy and repetition-with-alteration, which seems to be what lojban is trying to eliminate in its use.

Too much info, I'll stop there.

I do have two more questions if you have time.

#1 is historical: what's the process by which the core sets of things like spatial relationships or tenses or shapes or so on came to be enumerated?

EG: if I were doing a language in this form I'd go through all the languages I could get my hands on and try to get good lists of all their fundamental categories (eg: spatial prepositions and "classifiers", like you have in swahili and chinese (+ languages with heavy chinese contact) (cf: http://www.jstor.org/pss/413103 ) and then try to factor them into semantic atoms. I'd consider this approach bottom-up (see what's out there, and then try and simplify and unify them) and contrast it with a more top-down approach (trying to derive a finite set of spatial relations ab initio via pure reasoning); it'd also be a good set of "unit tests" for your final set of core concepts, making sure that none of these words' senses are not really expressible in terms of your base concepts.

How did the lojbanists derive their tenses / spatiotemporal prepositions / etc.? Is there a good "history of the design of lojban" that speaks to this?

Question #2: at a practical level how would you decompose "There are dogs in the kitchen" into lojban?

If I had to break it into predicates it'd probably be the conjunction:

- CONTAINS("containment-type T","kitchen","entity collection E")

- T ~ whatever containment type you have that is ~ "contains within its spatial bounds -- but not structurally -- for an indeterminate time period"

- COUNT(E) > 0

- ENTITY-COLLECTION-TYPE(E,X), where X ~ "collection treated as collection due to spatiotemporal circumstance and descriptive convenience" (EG: E is an entity collection b/c there are label(s) they all share, namely being instance-of dog and contained-in-the-kitchen in the same way; there's no assertion of any other source of entity-identity beyond the circumstances this utterance is describing; contrast to say "baseball team" or "deck of cards", etc., which are entity-collections with a more-persistent and "intentional" identity)

- forall e in E IS-INSTANCE-OF("instance-of-type IoT",e,"dog")

- "instance-of-type" ~ whatever instance-of you have that is ~ "is a concrete instantiation of an abstract type not otherwise specified (eg: an actual 'dog', not 'Pomeranian')

- + some temporal modifier to explain like "the described circumstance started before I made this utterance and I do not think it has ceased, yet"

...but I'd assume some of the intended distinctions are usually left implicit or inferred; what's a good lojban decomposition?