Product systemP3 · transformation fieldOperationraw → structuredOutputattribute · value · unitEvidenceAC820825
Attribute extraction

Turn Unstructured Product Information into Structured Attributes

Technical information often exists — just not in a format your catalog can use.

A product page may mention dimensions inside a paragraph. A supplier table may contain specifications under inconsistent labels. Documentation may describe materials and properties without mapping them into your PIM schema.

ENRIVAQ converts this information into structured product attributes.

See Attribute Extraction on Your Data
Reference agricultural spare part AC820825
AC820825REFERENCE PRODUCT · SAME-SKU EVIDENCE
As foundUNSTRUCTURED SOURCE

Outer diameter: AC820825; inner diameter: 8716106986118; width: Optima / Optima HD

TEXTTABLEDOCUMENTATION
ENRIVAQEXTRACT
Canonical recordSTRUCTURED OUTPUT
AttributeValueUnitStatus
{{ a.attr }}{{ a.val }}{{ a.unit }}structured
01
Input

Useful product data can be hidden almost anywhere

Attribute extraction can begin with unstructured or semi-structured information such as:

{{ c.label }}
AVAILABLE DOCUMENTATION

Technical content may describe dimensions and material in prose.

SPECIFICATION TABLES

Source terminology may use inconsistent labels for the same attribute.

PRODUCT DESCRIPTIONS

Outer diameter: AC820825; inner diameter: 8716106986118; width: Optima / Optima HD

For example

OEM AC820825; EAN 8716106986118; application Optima / Optima HD

contains useful technical data, but it is still just text until the values are separated into structured fields.
02
Extraction

Convert text into attribute, value and unit

The core output follows a simple structure: Attribute → Value → Unit

RAW TECHNICAL SOURCE
“Outer diameter AC820825; inner diameter 8716106986118; width Optima / Optima HD”
EXTRACTION FIELD
AttributeValueUnit
{{ e.attr }}{{ e.val }}{{ e.unit }}

This format allows downstream systems to work with the information as product data rather than as a sentence.

The exact attributes depend on the product category and target schema.

03
Mapping

Fit extracted data into the catalog you already use

Extraction is only useful when the output maps to the structure required by the business.

Source terminology{{ m.label }}
MAP
Canonical attributeOuter diameterOne field in the approved schema

The enrichment workflow needs to map source terminology into the approved attribute structure instead of creating a new field for every spelling variation.

04
Units

Keep values comparable across products

Different sources may use different units or formats. For example:

{{ u.src }}{{ u.val }}
SCHEMA-CONTROLLED OUTPUT42 mm

These may represent the same physical value, but they cannot be treated as two unrelated specifications.

Normalization allows the catalog to store technical values consistently. The target unit should be determined by the catalog schema.

The system should not convert units arbitrarily without clear rules.
05
Technical example

From technical text to a usable spare-part record

Use a real spare part here.

SOURCE INFORMATIONPublic source evidence: OEM reference · EAN · product type · compatibility · material
Agricultural spare part AC820825AC820825REFERENCE PRODUCT
Extracted attributes
{{ r.k }}{{ r.v }}

Visual: source on the left, structured record on the right. This is stronger than describing extraction conceptually.

Validation

Extraction should not automatically mean acceptance

A value can be extracted correctly from a source and still be unsuitable for the product record. Possible issues include:

These cases should move into validation or review rather than being silently published.
Extracted but not accepted{{ valLabel }}
{{ v.name }}{{ v.tag }}review

Turn one unstructured product into a structured record

Send a representative product or technical source and see what can be extracted.

See It on Your Data

Source discovery·Data enrichment

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