Having "bold" mean some semantics, e.g., important.

Then they merge. Alice does not consider it important, Bob does -> render both. E.g., Bob's "importance" expressed as bold, Alices "not important" as grayed text.

E.g.,

"Ny is a great city."

Alice removes "great".

Bob wonts to replace it with "gorgeous", by removing "reat" and adding "orgeous".

Having merged:

"Ny is a orgeous city."

Begs for semantic intent preservation, such as "reword great to gorgeous".

Uhh, I'd imagine "remove" would refer to "bold" annotation.

Otherwise, there can be another "bold" with t < 20, that would be accidentally removed.

Syntactic intent is not preserved.

That would be better for user to decide.

I think a good default is to express semantics explicitly.

I.e., for Bob to not automatically state his utterance as important just because it's atop of Alice's, that she considers important.

If Bob tries to reword - ok. If Bob want to add - no.

Given Bold, Italic, Colored are syntactic representation of semantics that we do capture - they can overlap.

Moreover, in Bob's user-defined mapping from semantics to syntax, Bob's "important" can be bold, while Alice's "important" can be italic.

Again, let them capture semantics.

Say, "Alice considers "The fox jumped"" as important. Alice changes mind, only "The" is important. Bob considers "jumped" as important.

Result: Alice considers "The" important. Bob considers "jumped" important.

Color is meant to convey some semantics. Like "accent", or "important". These semantics can coexist, just like italic and bold.

So a solution may be to: 1. Let users express semantics of their annotations 2. Give user-customizable defaults of how they are to be rendered.

Ensuring, that semantics's render is composable. I.e., it conveys originally asigned semantics.

Good remark of syntactic vs semantic intent preservation.

Semantics are in the head of a person, that conveys them as syntactic ops. I.e., semantics get specified down to ops.

Merging syntactically may not always preserve semantics. I.e., one wants to "make defs easier to read by converting them to CamelCase", another wants the same but via snake-case. Having merged them syntactically, we get Camel-Snake-Case-Hybrid, which does not preserve any semantic intent. The semantics intent here are not conflict-free in the first case, though.

Make defs readable | | as CamelCase as Snake Case | | modify to CC modify to SC They diverged at this point, even before getting to syntactic changes.

The best solution would be to solve original problem in a different way - let defs be user-specific. But that's blue sky thinking. Although done in Unison, we do have syntactic systems around.

So staying in a syntactic land, the best we could do is to capture the original intent: "Make defs readable".

Then we need a smart agent, human or an AI, specify it further.

I.e., let's capture user's intent as ops, not their result.

I have a separate theory here...

but where does even "deliberate intent" ultimately come from?

Nicastri, C., & Kumar, P. (2022, February 11). Psychosocial, economic, and mental health predictors of COVID-19 vaccine intent. https://doi.org/10.31234/osf.io/snrgf

de Figueiredo, A., & Larson, H. J. (2021). Exploratory study of the global intent to accept COVID-19 vaccinations. Communications Medicine, 1(1), 1–10. https://doi.org/10.1038/s43856-021-00027-x

There's something interesting in this take on writing.

It also brings up the looming question: "What is your intent?"

Agarwal, A. (2021). The Accidental Checkmate: Understanding the Intent behind sharing Misinformation on Social Media. PsyArXiv. https://doi.org/10.31234/osf.io/kwu58

NW, 1615 L. St, Suite 800Washington, and DC 20036USA202-419-4300 | Main202-857-8562 | Fax202-419-4372 | Media Inquiries. ‘Intent to Get a COVID-19 Vaccine Rises to 60% as Confidence in Research and Development Process Increases’. Pew Research Center Science & Society (blog), 3 December 2020. https://www.pewresearch.org/science/2020/12/03/intent-to-get-a-covid-19-vaccine-rises-to-60-as-confidence-in-research-and-development-process-increases/.

Barnby, J. M., Bell, V., Mehta, M., & Moutoussis, M. (2020, April 17). Reduction in social learning and policy uncertainty about intentional social threat underlies paranoia: evidence from modelling a modified serial dictator game. https://doi.org/10.31234/osf.io/jvx5y

目标是根据一个用户utterance/query 得到其对应的语义slot。slots是预先根据场景定于的。通常来说有两种类型的表示，一个是句子级别的类别，例如用户的意图和utterance的类别。另外一个是单词级别的信息抽取，例如命名实体和槽位填充。

意图识别是根据一句话来检测用户的意图。 基于深度学习的意图识别： L. Deng, G. Tur, X. He, and D. Hakkani-Tur. Use ofkernel deep convex networks and end-to-end learningfor spoken language understanding. InSpoken Lan-guage Technology Workshop (SLT), 2012 IEEE, pages210–215. IEEE, 2012

G. Tur, L. Deng, D. Hakkani-T ̈ur, and X. He. Towardsdeeper understanding: Deep convex networks for se-mantic utterance classification. InAcoustics, Speechand Signal Processing (ICASSP), 2012 IEEE Interna-tional Conference on, pages 5045–5048. IEEE, 2012.

D. Yann, G. Tur, D. Hakkani-Tur, and L. Heck. Zero-shot learning and clustering for semantic utteranceclassification using deep learning. 2014.

尤其是这个用CNN来抽取query vector进行query分类。 H. B. Hashemi, A. Asiaee, and R. Kraft. Query intentdetection using convolutional neural networks. InIn-ternational Conference on Web Search and Data Min-ing, Workshop on Query Understanding, 2016

P.-S. Huang, X. He, J. Gao, L. Deng, A. Acero, andL. Heck. Learning deep structured semantic modelsfor web search using clickthrough data. InProceedingsof the 22nd ACM international conference on Confer-ence on information & knowledge management, pages2333–2338. ACM, 2013

Y. Shen, X. He, J. Gao, L. Deng, and G. Mesnil.Learning semantic representations using convolutionalneural networks for web search. InProceedings of the23rd International Conference on World Wide Web,pages 373–374. ACM, 2014.

Intent is the critical factor for design work, not its function.

How is political activism being modeled for these youths? Was there intent participation from which they can observe and learn until they built confidence to proceed independently or were they expected to figure it out on their own with minimal guidance? This is a departure from the examples we have been looking at until now.

and therefore intent?

Maybe the facade of moral character, but if used just because Aristotle's guidebook told the speaker to... I'd question that, anyway.

When intent matters, rather than outcome.