standOff, and the article is at its publisher via the link below. When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote for that row; on this page it is withheld with the article, and the article is at its publisher. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.| relation to other work | claim_relations | how this paper stands to another: agrees, contradicts, extends, qualifies |
| claim type | claim_type | the shape of the claim: existence, mechanism, method, critique, prediction, null |
| concept edge | concept_edges | an asserted relation between two concepts, with the sentence asserting it |
| concept | concepts | an idea the paper works with, quoted where the paper uses it |
| content tag | content_tags | a finding, definition, quantity, statistic or variable named in the paper |
| limitation | limitations | what the paper says its evidence cannot support |
| mechanism | mechanisms | how the reported effect is said to come about |
| method | method | how the paper produced its evidence |
| phenomenon | phenomenon | the effect or regularity under study |
| sense | senses | a distinct use of a term, quoted where the paper fixes it |
Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; none of 1 relation here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.
This record holds no controls. A layer is empty when the tagger recorded nothing in it — which is not the same as the paper having nothing to record.
| facet | tag | field | conf. | whose words |
|---|---|---|---|---|
| claim_type | existence Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_type | the paper's words | |
| phenomenon | corpus-based typology Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | phenomenon | the paper's words | |
| method | review Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: review | method | the paper's words | |
| mechanisms | mechanisms Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[0] | the tagger's words | |
| mechanisms | mechanisms Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[1] | the tagger's words | |
| mechanisms | mechanisms Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | mechanisms[2] | the tagger's words | |
| limitations | The authors' own exploratory comparison of noun-phrase lengths in Universal Dependencies versus Multi-CAST is presented as preliminary. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: the DLM comparison specifically: MORE DETAILED INVESTIGATIONS ARE REQUIRED, these being INITIAL OBSERVATIONS | limitations[0] | the tagger's words | |
| limitations | Corpus representativeness is identified as the field's most pressing unsolved problem. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: every crosslinguistic corpus result in the field: THE MOST PRESSING ISSUE IN CBT IS THE REPRESENTATIVENESS OF CORPORA USABLE FOR CROSSLINGUISTIC RESEARCH | limitations[1] | the tagger's words | |
| limitations | Spoken and especially interactional language use is badly under-represented in available corpora. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: any claim about spoken or conversational language: THERE IS A BLATANT SHORTAGE OF SPOKEN-LANGUAGE DATA FROM A LARGER RANGE OF LANGUAGES, [and] EVEN LESS INTERACTIONAL LANGUAGE USE | limitations[2] | the tagger's words | |
| limitations | The review names its field's outstanding problem as the corpora themselves: they are not yet crosslinguistically representative, and spoken or signed texts are what is missing. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: any crosslinguistic generalisation drawn from these corpora: the review names more representative corpora including spoken or signed texts as a remaining challenge for the field | limitations[3] | 1.0 | the tagger's words |
| limitations | The texts that would be comparable are frequently not obtainable, and copyright is named as one of the reasons, so what can be compared is set by access rather than by the research question. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. what this limits: the coverage of stimuli-based elicited texts in this field: they are crucial for projects needing comparability, and the review states they are rarely published as organized web-accessible corpora and often not openly accessible | limitations[4] | 1.0 | the tagger's words |
| concepts | corpus-based typology Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: corpus-based typology | concepts[0] | the paper's words | |
| concepts | utterance populations Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: utterance populations | concepts[1] | the paper's words | |
| concepts | grammar-based typology Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: grammar-based typology | concepts[2] | the paper's words | |
| senses | language - AS A POPULATION OF UTTERANCE TOKENS: the corpus-based conception, in which an individual corpus is a SAMPLE of that population rather than the language itself Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[0] | 1.0 | the tagger's words |
| senses | language - AS A MONOLITHIC ENTITY shared by all members of a speech community: the conception the corpus-based view is explicitly defined against Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[1] | 1.0 | the tagger's words |
| senses | word order - a CATEGORICAL property in some languages and a probabilistic one in most: Tamil at 0% and Arabic at 100% VO, while most languages show variability with a preference Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | senses[2] | 1.0 | the tagger's words |
| claim_relations | builds-on → Haig et al. (2011) Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_relations[0] | the tagger's words | |
| claim_relations | contradicts → Du Bois (1987) discourse ergativity Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | claim_relations[1] | the tagger's words | |
| concept_edges | corpus-based typology —contrasted-with→ grammar-based typology Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. strength of the relation: 1 also in: corpus-based typology · grammar-based typology | concept_edges[0] | the tagger's words | |
| content_tags | regression Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: regression | content_tags.statistics[0] | the tagger's words | |
| content_tags | mean Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: mean | content_tags.statistics[1] | the tagger's words | |
| content_tags | standard deviation Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: standard deviation | content_tags.statistics[2] | the tagger's words | |
| content_tags | Corpus-based typology largely reproduces the classifications of grammar-based typology, but adds finer-grained, quantitatively explicit detail and robustness. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[0] | the tagger's words | |
| content_tags | In the authors' own comparison, long noun phrases are far commoner in the written Universal Dependencies corpora (about 36% of NPs at least four dependencies long) than in the spoken Multi-CAST corpora (about 12%). Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[1] | the tagger's words | |
| content_tags | Spoken texts seem to lack the prerequisite for DLM effects: phrases or local dependency trees long enough for dependency length to matter. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[2] | the tagger's words | |
| content_tags | Across 12 spoken corpora, subjects inside a same-subject reference chain are about 15-20% likelier to be realised as zero than subjects elsewhere, regardless of the language's overall zero rate. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[3] | the tagger's words | |
| content_tags | Nearly every language with a zero-subject rate above 70% has fully grammaticalised, transparent subject agreement, the exceptions being Mandarin and Jinghpaw. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[4] | the tagger's words | |
| content_tags | Haig & Schnell (2016) and Schnell et al. (2021) find no support for discourse ergativity: S shows a lower rate of newness and full-NP expression than P. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[5] | the tagger's words | |
| content_tags | Slower articulation and pausing are significantly more likely just before nouns than before verbs. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[6] | the tagger's words | |
| content_tags | Word-order entropy trades off against case marking: the less confusable subject and object are by case, the freer their relative order. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[7] | the tagger's words | |
| content_tags | The largest annotated multilingual resource is typologically skewed - 24 million tokens across 104 languages, more than half of them Indo-European. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[8] | the tagger's words | |
| content_tags | Spoken-language data are scarce in corpus-based typology, and conversational data scarcer still. Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.findings[9] | the tagger's words | |
| content_tags | corpus-based typology (CBT) Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: corpus-based typology (CBT) | content_tags.definitions[0] | the tagger's words | |
| content_tags | grammar-based typology (GBT) Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: grammar-based typology (GBT) | content_tags.definitions[2] | the tagger's words | |
| content_tags | parallel text corpora Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: parallel text corpora | content_tags.definitions[3] | the tagger's words | |
| content_tags | parallax text corpora Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: parallax text corpora | content_tags.definitions[4] | the tagger's words | |
| content_tags | original text corpora Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: original text corpora | content_tags.definitions[5] | the tagger's words | |
| content_tags | dependency length minimization (DLM) Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: dependency length minimization (DLM) | content_tags.definitions[6] | the tagger's words | |
| content_tags | discourse ergativity Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: discourse ergativity | content_tags.definitions[7] | the tagger's words | |
| content_tags | NP length Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: NP length | content_tags.variables[1] | the tagger's words | |
| content_tags | proportions of zeros Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. also in: proportions of zeros | content_tags.variables[2] | the tagger's words | |
| content_tags | 36% ... 12% — share of noun phrases at least four dependencies long in the written UD corpora versus the spoken Multi-CAST corpora Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[0] | the tagger's words | |
| content_tags | 15–20% — extra likelihood that a chain-medial subject is zero rather than a pronoun, compared with subjects outside a same-subject chain Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[1] | the tagger's words | |
| content_tags | β1 = 0.84 — regression coefficient of the fit relating zero rates inside versus outside same-subject chains, with intercept 24.77 Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[2] | the tagger's words | |
| content_tags | 1,257 — languages covered by the Parallel Bible Corpus, averaging 10,707 verses per language Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[3] | the tagger's words | |
| content_tags | 464 — languages for which a Universal Declaration of Human Rights translation exists, averaging 1,694 words each Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[4] | the tagger's words | |
| content_tags | 24 million — word tokens in Universal Dependencies v2.7, spread over 104 languages of which over half are Indo-European Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[5] | the tagger's words | |
| content_tags | 131,574 — mean word-token size of an individual language corpus in Universal Dependencies Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[6] | the tagger's words | |
| content_tags | 143 ... 74 — UD corpora, and languages they come from, used in the authors' own NP-length analysis after excluding 37 with under 1,000 data points Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above. | content_tags.quantities[7] | the tagger's words |
Tags that could not be placed in the text:
What was deliberately not tagged, and why, is recorded per paper by the tagger. Where a paper has no such record, this page says so rather than implying that nothing was declined.