ek.metrics.fields

Field-level metric for record / dict-shaped extractions.

Compares two flat records key by key into precision / recall / F1, with a wrong value counting as both a spurious prediction and a missed gold (the conventional slot-error accounting). It is dependency-free, so it ships in core for the common “compare these two extracted records” case; the tag-sequence span metrics (seqeval / nervaluate, with their explicit match schemes) and nested metrics (ANLS*) arrive behind the [metrics] extra – see misc/docs/ek_02.

Aggregation is micro-averaged over the corpus (sum TP/FP/FN, then divide), carried in each Score’s detail so evaluate() does it correctly rather than averaging per-record F1s.

Classes

FieldMetric(*[, canonicalizer])

Per-field precision/recall/F1 for two dict records.

class ek.metrics.fields.FieldMetric(*, canonicalizer=None)

Bases: object

Per-field precision/recall/F1 for two dict records.

Parameters:

canonicalizer – Optional str -> str applied to string values before comparison (e.g. casefold/whitespace folding).

aggregate(scores)

Micro-averaged F1 over the corpus (sum TP/FP/FN, then divide).

Return type:

float