Sentence examples for lenient matching from inspiring English sources

(2009) by two curators for a subset of the documents and reached 90.7% and 96.7% for strict and lenient matching, respectively.

For comparison, a baseline method that used our dictionary and dictionary matching typically used for NER (we used LINNAEUS [ 7]) achieved notably lower values (F1-score of 38%and5454% for strict and lenient matching respectively).

The results for both strict (requires exact matching between annotations by the gold standard and annotations by PathNER) and lenient matching (annotations by PathNER that overlap with the gold standard are accepted) are presented in Table 5. PathNER achieves a lenient F1-score of 84%.

There is generally a trade-off between the proportion of missing geocodes and geocode accuracy; lenient match rates tend to increase the proportion of successfully geocoded addresses at the expense of geocode accuracy [ 6].

For lenient evaluation, recall improved from 58% (rule-based) and 63% (soft dictionary matching) to 88% (hybrid), while keeping precision at an acceptable level (81%).

If findings that rub liberals the wrong way can't be reviewed impartially — and if those that match their ideals are given more lenient treatment — we have a problem.

Two types of evaluations are performed: exact comparison (meaning that the span of a proposed brain region must exactly match a manually annotated brain region) and lenient comparison (meaning that the span of an identified brain region may be equal or smaller than a manually annotated brain region).

Criteria (1) to (3) will be matched 1 1; criteria (4) & (5) are used as lenient criteria, to be matched 1 1 if possible, otherwise the extremes may not be matched together.

Retailers will often match or double their pre-order sales for on-site inventory – so even if we're lenient with the numbers, we very well could be talking about a total inventory of 5 to 6 thousand handsets.

We choose the standard scoring procedure in the action memory literature [ 10, 49], where strict scoring is used for the nouns (exact matches were required) and lenient scoring is used for verbs (where non-exact matches are scored as correct).

With respect to this, DAMAlign [ 25] is proposed in our previous work, which takes both dividing-and-matching strategies and the same lenient criteria as AlignNemo to locally extend a pair of homologous protein pairs.