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Intent Classification datasets
archive 2025-07-28
14 datasets carry the task tag "Intent Classification" (the task itself: Intent Classification), ordered by the archive's paper count. Page 1 of 1: 14 shown of 14. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Intent Classification datasets 1–14 of 14
SLURP (Spoken Language Understanding Resource Package)
A new challenging dataset in English spanning 18 domains, which is substantially bigger and linguistically more diverse than existing datasets.
106 papers · 2 benchmarks
This dataset is for evaluating the performance of intent classification systems in the presence of "out-of-scope" queries, i.e., queries that do not fall into any of the system-supported intent classes.
87 papers · 5 benchmarks
MASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations for the Natural Language Understanding tasks of intent prediction and slot annotation.
72 papers · 3 benchmarks
xSID (Cross-lingual Slot and Intent Detection)
xSID, a new evaluation benchmark for cross-lingual (X) Slot and Intent Detection in 13 languages from 6 language families, including a very low-resource dialect, covering Arabic (ar), Chinese (zh), Danish (da), Dutch (nl), English (en),…
18 papers · 0 benchmarks
KUAKE-QIC (Query Intent Classification Dataset)
KUAKE Query Intent Classification, a dataset for intent classification, is used for the KUAKE-QIC task.
14 papers · 1 benchmark
A dataset with a single banking domain, includes both general Out-of-Scope (OOD-OOS) queries and In-Domain but Out-of-Scope (ID-OOS) queries, where ID-OOS queries are semantically similar intents/queries with in-scope intents.
6 papers · 1 benchmark
A dataset with two separate domains, i.e., the "Banking'' domain and the "Credit cards'' domain with both general Out-of-Scope (OOD-OOS) queries and In-Domain but Out-of-Scope (ID-OOS) queries, where ID-OOS queries are semantically similar…
3 papers · 0 benchmarks
ViMQ is a Vietnamese dataset of medical questions from patients with sentence-level and entity-level annotations for the Intent Classification and Named Entity Recognition tasks.
3 papers · 0 benchmarks
ORCAS-I (Queries Annotated with Intent using Weak Supervision)
A labelled version of the ORCAS click-based dataset of Web queries, which provides 18 million connections to 10 million distinct queries.
2 papers · 1 benchmark
arXivEdits an annotated corpus of 751 full papers from arXiv with gold sentence alignment across their multiple versions of revision, as well as fine-grained span-level edits and their underlying intentions for 1,000 sentence pairs.
2 papers · 0 benchmarks
MIPD (Manipulation and Intention In a Novel Corpus of Polish Disinformation)
A novel corpus of 15,356 Polish web articles, including articles identified as containing disinformation.
1 paper · 0 benchmarks
Search4Code is a large-scale web query based dataset of code search queries for C# and Java.
1 paper · 0 benchmarks
Skit-S2I (Skit-S2I: An Indian Accented Speech to Intent dataset)
This dataset for Intent classification from human speech covers 14 coarse-grained intents from the Banking domain.
1 paper · 0 benchmarks
Dataset for our paper Disambiguation-Centric Finetuning Makes Enterprise Tool-Calling LLMs More Realistic and Less Risky which includes 5000 enterprise tools and the corresponding dialogues generated using DiaFORGE UTC data engine.
1 paper · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.