TREC 2023 Interactive Knowledge Acquisition Track dataset
Data e Risorse
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Training topics
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Test Topics
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Supporting documents relevance judgmentsTEXT
2023-qrels.all-turns.txt
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Personal Text Knowledge Base (PTKB) relevance judgmentsTEXT
2023-ptkb-qrels.txt
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Corpus - ClueWeb22-B
obtain.php
| Campo | Valore |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode | {006:55} |
| catalog_@context | https://project-open-data.cio.gov/v1.1/schema/data.json |
| catalog_conformsTo | https://project-open-data.cio.gov/v1.1/schema |
| catalog_describedBy | https://project-open-data.cio.gov/v1.1/schema/catalog.json |
| identifier | ark:/88434/mds2-3261 |
| issued | 2024-09-26 |
| landingPage | https://data.nist.gov/od/id/mds2-3261 |
| language | {en} |
| license | https://www.nist.gov/open/license |
| modified | 2024-05-09 00:00:00 |
| programCode | {006:045} |
| publisher | National Institute of Standards and Technology |
| references | {https://trec.nist.gov/pubs/trec32/papers/Overview_ikat.pdf} |
| resource-type | Dataset |
| source_datajson_identifier | true |
| source_hash | 0e84446f029163a580d7b4180cd7f4621f627dc5f69a067a2acddb8d20ae3908 |
| source_schema_version | 1.1 |
| theme | {"Information Technology:Data and informatics"} |
| Gruppi |
|
| Tag |
|
| isopen | False |
| license_id | other-license-specified |
| license_title | other-license-specified |
| maintainer | Ian Soboroff |
| maintainer_email | ian.soboroff@nist.gov |
| metadata_created | 2025-09-23T14:16:35.886517 |
| metadata_modified | 2025-09-23T14:16:35.886524 |
| notes | iKAT is the successor to the TREC Conversational Assistance Track (CAsT). The fourth year of CAST aimed to add more conversational elements to the interaction streams, by introducing mixed initiatives (clarifications, and suggestions) to create multi-path, multi-turn conversations for each topic. TREC iKAT evolves CAsT into a new track to signal this new trajectory. iKAT aims to focus on supporting multi-path, multi-turn, multi-perspective conversations. That is for a given topic, the direction and the conversation that evolves depends not only on the prior responses but also on the user. |
| num_resources | 5 |
| num_tags | 9 |
| title | TREC 2023 Interactive Knowledge Acquisition Track dataset |