技能 人工智能 自然语言与语言理论期刊指南

自然语言与语言理论期刊指南

v20260724
natural-language-and-linguistic-theory
本技能是为计划向《自然语言与语言理论》(NLLT) 投稿的理论语法或形态学文章作者提供的详细指南。它详细介绍了期刊对稿件的严格要求,核心在于论证的正式分析必须以丰富、具有代表性的跨语言实证数据为坚实基础。使用本工具评估您的稿件是否满足NLLT高标准的严谨性、适用范围和结构要求。
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Natural Language & Linguistic Theory (natural-language-and-linguistic-theory)

Journal positioning

Natural Language & Linguistic Theory (NLLT), published by Springer, is a leading venue for theoretical linguistics — especially syntax and morphology — distinguished by its insistence that formal analyses be tested against rich, often cross-linguistic empirical data. Its defining expectation is a theoretical proposal that is both formally explicit and deeply grounded in careful language description: the analysis must earn its keep on detailed data, frequently from less-studied languages, and yield consequences for grammatical theory. A formalism-driven paper that is thin on data, or a description with no theoretical proposal, is a poor fit. This skill is a fit / venue-selection / re-framing aid. It does not replace the journal's current submission guidelines. Before submitting, re-check the live NLLT author instructions, and defer all reporting specifics to the official page.

When to trigger

  • The author names NLLT for a theoretical syntax or morphology article grounded in detailed language data.
  • A formal proposal must be strengthened with richer, more representative cross-linguistic empirical support.
  • The author is choosing between NLLT and a more formalism-focused or generalist venue.
  • The author needs NLLT's empirical-grounding bar and desk-reject heuristics.

Scope & topic fit

  • Theoretical syntax: clause structure, movement, case and agreement, argument structure, ellipsis, locality — argued on detailed data.
  • Theoretical morphology and the morphology–syntax interface, including word-formation and inflectional systems.
  • In-depth analyses of individual languages (often less-studied) that yield general theoretical consequences.
  • Comparative and microcomparative studies where dialect or language variation tests a theoretical proposal.
  • Interface work (syntax–semantics, morphology–phonology) where the empirical base is central to the argument.

Method & evidence bar

  • The contribution is a formally explicit proposal grounded in rich language data; the analysis and its theoretical consequences are stated clearly and early.
  • Empirical grounding is the differentiator: data must be detailed, representative, and carefully sourced — judgments, paradigms, and patterns from primary or well-documented description, with reporting specifics deferred to the official guidance.
  • Cross-linguistic or microcomparative evidence is used to test, not merely decorate, the proposal; the data genuinely discriminate among analyses.
  • The formal analysis is consistent, derivations or feature systems are shown, and predictions are falsifiable and checked.
  • Alternative analyses are weighed and shown to be less adequate against the data.
  • Data are transparent: numbered examples with morpheme-by-morpheme interlinear (Leipzig-style) glosses, translations, and sources; fieldwork data are attributed.

Structure & house style

  • Full-length theoretical article with detailed data sections and a sustained formal argument; re-check current length limits and article types on the live guide.
  • Citation follows the journal's current Springer author-date style with a reference list; formal notation is defined and consistent.
  • Double-blind review: anonymize the manuscript (self-citations and acknowledgements) per current policy.
  • Numbered examples with aligned interlinear glosses, translations, and sources, in the journal's format; IPA where phonetic detail matters.
  • Trees, feature matrices, and tables meet the journal's specifications and remain legible in print.

Official-submission checklist

  • Before giving submission-ready advice, read ../../resources/source-basis.md and ../../resources/official-source-map.md; start from the Springer anchors, then cite the current NLLT page you checked.
  • Search the live site for "Natural Language Linguistic Theory submission guidelines" and follow the current Springer version.
  • Re-check article types, length limits, and the abstract requirement.
  • Confirm the Springer citation/notation style and anonymization for double-blind review.
  • Re-check the example/glossing format, data sourcing/attribution, and any fieldwork elicitation-ethics expectations.
  • Re-check competing-interest, funding, and AI-use disclosures.
  • If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

  • The formal proposal is grounded in detailed, representative language data, not asserted on sparse examples.
  • Cross-linguistic or microcomparative data genuinely test the proposal.
  • Theoretical consequences for syntax/morphology are stated explicitly.
  • Derivations or feature systems are shown and predictions are falsifiable.
  • Numbered examples carry Leipzig-style glosses, translations, and proper sources.
  • The manuscript is anonymized and follows the current Springer style.

Common desk-reject triggers

  • A formalism-driven analysis thin on data or resting on sparse, non-representative examples.
  • A rich description with no theoretical proposal or consequence.
  • Data that do not actually discriminate the proposal from leading alternatives, or ignoring strong competing analyses and established cross-linguistic results.
  • Fieldwork or primary data without attribution, glossing, or translation.
  • Scope or generality overstated relative to the empirical base provided.

Re-routing decision

  • Generative syntax/interface argument that is theory-internal and data-light → linguistic-inquiry.
  • Discipline-wide result across subfields, incl. experimental → language (LSA).
  • Framework-neutral general theoretical linguistics → journal-of-linguistics.
  • Formal semantics or philosophy-of-language argument of philosophical interest → the-philosophical-review.
  • Discipline-wide descriptive/typological result with broad significance → language.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] Natural Language & Linguistic Theory
[Area] <syntax / morphology / interface>
[Claim] <the formal proposal in one line>
[Data/framework] <does the cross-linguistic empirical grounding clear NLLT's data bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <length / Springer style / anonymization / glossing / data sourcing + ethics>
[Re-route suggestion] <if not a fit, a better-matched venue>
信息
Category 人工智能
Name natural-language-and-linguistic-theory
版本 v20260724
大小 6.83KB
更新时间 2026-07-28
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