Language Log

This morning's question:

I'm an ESL textbook editor in Korea, and a grammar dispute has come down to one question: is "What do you say that we get together tonight?" grammatical, with "that" included (vs. the more common zero-complementizer "What do you say we…")?

My understanding is "that" is simply optional here, not ungrammatical.

Email from JK:

My daughter remarked that on several occasions recently she has heard presumably college-educated people use the word “I’s”, in a sentence like "I just picked up Margaret and I’s cat from the vet."

I'm guessing the reason for this jarring (to me) usage is that the sentence could be more logically parsed as

I just picked up Margaret and (my cat) from the vet  than as
I just picked up (Margaret and my) cat from the vet.

The brain turns to I just picked up Margaret and I’s cat from the vet as a solution because because Margaret and I is a strong connection like my cat, and it's encountered first in the sentence.

So it's parsed as I just picked up (Margaret and I)’s cat from the vet.

That sounds awful, but is it acceptable usage (obligatory SMBC reference)?

According to a recent BoingBoing segment,

Ballots for a special election in England's Clacton-by-Sea are the longest ever produced in U.K. electoral history despite¹ only one major party contesting the race.

The footnote:

1. This is the journalist's despite, wherein the word implies disregard when there is in fact a blatant causal relationship.

The singularity may have arrived, but AI systems still can't label diagrams:

As you probably know, Emily Wilson wrote a critical review of Christopher Nolan's Odyssey movie, and Joyce Carol Oates posted a negative evaluation of Wilson's review, among lots of other (mass and social) media coverage.

My favorite so far is today's SMBC:

Last December, Rob Pike got big mad at AI Village. Simon Willison covered the associated events and discussions.

I've recently wrestled several times with similarly frustrating Gmail searches, for recent tickets and the like:

Impossible to put into words how useless Gmail search is. No wait, these guys did it!

[image or embed]

— Alex Selby-Boothroyd (@alexselbyb.bsky.social) July 28, 2026 at 2:22 PM

I get the impression that these problems have multiplied since Gemini started helping out in Gmail, but I might be wrong.

Randoh Sallihall at unscramblerer.com sent an email offering his company's 2026 study of "America's most searched words" — what he sent is presented verbatim below.

In a July 23 Memorandum Decision from the Court of Appeals of Indiana (noted by Robert Freund and 404 Media), Judge Jeffrey L. Marchal complains that

The Transcript contains various types of errors. There are numerous typos that change the meaning of the testimony, question, or objection. See, e.g., Tr. Vol. II at137:18, 144:10, 147:10; Tr. Vol. III at 6:13. In some instances, witnesses’ and trial attorneys’ names are reported incorrectly. Tr. Vol. II at 220:5; Tr. Vol. III at 142:15–20, 143:15, 162:4–5. At one point in the Transcript, a motion, presumably made by the State, is attributed to the trial court. Tr. Vol. II at 107–08. At another point, an objection, presumably made by Williams, is attributed to the Bailiff. Tr. Vol. II at 177:15. At yet another point, the State’s closing argument is attributed to the trial court. Tr. Vol. III at 228:1. […]

Based upon the types of errors reviewed, it appears that generative artificial intelligence may have assisted with the preparation of this transcript. While AI can improve efficiency and be a productive tool for many professionals, it is incumbent upon those using such systems to proofread and ensure the accuracy of the generated product.

Today's SMBC:

On July 5, Phil Resnik delivered a keynote address at the 64th Annual Meeting of the Association for Computational Linguistics, with the title "A New Balancing Act: Reflections on the Relationship between Computational Linguistics and AI":

In this talk I argued that the field of computational linguistics – a term that includes NLP as its engineering-research subdiscipline – is experiencing a “success catastrophe”. The commercial success of LLM-based AI has thrown three key aspects of our research community out of balance. Here are three balancing acts we face:

First: Like any research community, we can recognize and take advantage of the knowledge obtained in earlier generations of work; we can also lean into new approaches.

Second: We can focus on language as language, which is to say, the properties of language that make it distinctive and human; we can also treat language as an input/output modality for AI systems.

Third: We can emphasize our role as a research community, where our primary purpose is to contribute to the stock of human knowledge; we can also emphasize our role in making sure that our young members have a path forward to get jobs – particularly jobs in industry since the path into academia is never a sure bet and for many of them industry is the goal.

In each of these pairings, the central importance of the former has given way to the overwhelming dominance of the latter.

Following up on our recent post about generational punctuation differences, here's a cartoon from the 7/27 New Yorker:

Below is a guest post by Richard Sproat and Rafael Núñez. It summarizes a recently published paper by d’Errico, Santos da Rosa, Courtenay,  Núñez,  Liu,  Sproat, & Blasi,  "Inferring Conventional Sign Systems from Paleolithic Engravings: Methodological and Theoretical Challenges".

Back in February, Christian Bentz and Ewa Dutkiewicz (henceforth BD) published a paper in the Proceedings of the National Academy of Sciences, that presented their study of markings on Paleolithic artifacts, mostly in bone, antler and ivory, from the Swabian Aurignacian (43,000–34,000 BP). Their conclusion, based on various statistical analyses, including entropic measures, and a couple of sign repetition rate measures, was that these marks constituted a structured system of deliberate and conventional signs. By translating the engravings into 1D sequences of standardized characters, they reported strong statistical overlap with early Mesopotamian protocuneiform (Uruk V) and clear divergence from later systems as well as modern writing systems.