WKS - Training model to identify entities on tables

Question

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We are trying to train our model to identify values from multiple types of tables whom contain different number of rows and columns. A text row was extracted to begin the training, first we configure our system types and then, marked the entities and also the relation “AllInOne”. We are able to train 10 relations in a training set, but when the model is tested, we are only able to see 8 relations even creating other document sets for training and test the model multiple times. Is there another way to associate the column value with the row values in a single relation considering there isn’t a standard for the types of tables we are analyzing with the Discovery service?

We are expecting the discovery service response as the following:

"relations": [
    {
        "type": "AllInOne",
        "sentence": "…",
        "arguments": [
            {
                "entities": [
                    {
                        "“text": "””",
                        "type": "entity1"
                    }
                ]
            },
            {
                "entities": [
                    {
                        "“text": "””",
                        "type": "entity2"
                    }
                ]
            },
            {
                "entities": [
                    {
                        "“text": "””",
                        "type": "\"entity..n”,"
                    }
                ]
            },
            { "..." }
        ]
    }

Answer 1

The machine learning model that is trained in Watson Knowledge Studio targets unstructured natural language text. It may not be suitable for (semi-) structured format like table, especially for relations.