Entity Resolution

These tasks consume Text and produce Text containing a resolved name or identifier. Both use configured language and embedding models, so they require their provider credentials and reference data.

LLMCanonicaliser

Matches text against an entity file using embedding retrieval and an LLM. Configure model, entities (a text file containing one entity per line), and a template using the input name and {entities} for retrieved candidates. embedding_model and count control candidate retrieval.

Commands: run only, with the shared run options:

collectra --pipeline pipeline.yaml task canonicalise run results/page001.collectra --usage
collectra --pipeline pipeline.yaml task canonicalise run --help

Here canonicalise is the configured name of a collectra.LLMCanonicaliser task. There is no train command.

IRNResolver

Resolves text to an IRN identifier from an Excel reference file. Configure type: collectra.IRNResolver, model, source (the workbook), card_template (reference-row fields), and query_template (input Text names). Additional controls include irn_column, index_filters, count, score_floor, and score_gap_eps. The task builds or loads retrieval indexes, and returns empty text if it finds no accepted match.

Commands: run only, with the shared run options:

collectra --pipeline pipeline.yaml task resolve_irn run results/page001.collectra --usage
collectra --pipeline pipeline.yaml task resolve_irn run --help

Here resolve_irn is the configured task name. There is no standalone CLI command for training or rebuilding indexes.