14. Success Criteria

14.1. Technical Metrics

14.1.1. Search Performance

Metric

Target

Measurement Method

Vector search latency (p95)

<100ms

Elasticsearch slow log analysis

kNN recall@10

>85%

Evaluation on curated test set

Text search latency (p95)

<50ms

Elasticsearch slow log analysis

Completion suggest latency (p95)

<20ms

Elasticsearch slow log analysis

Query error rate

<0.1%

Application error logging

14.1.2. Index Quality

Metric

Target

Measurement Method

Embedding coverage

>99% of toponyms

Field existence query

Cross-reference coverage

>50% of places

Relations field analysis

Duplicate rate

<1%

Clustering analysis

14.1.3. Training Data Quality

Metric

Target

Measurement Method

Training candidate coverage

>50% of languages

Language distribution analysis

Cluster purity

>90%

Manual spot-check of sample clusters

Triplet validity

>95%

Validation against known equivalents

14.1.4. Operational

Metric

Target

Measurement Method

Index uptime

>99.9%

Cluster health monitoring

Snapshot success rate

100%

Snapshot status API

Reindex duration

<24 hours

Job timing logs

Recovery time objective

<1 hour

Restore drill timing

14.2. User Experience Metrics

14.2.1. Search Quality

Metric

Target

Measurement Method

Relevant results in top 10

>80%

User evaluation study

Cross-lingual match success

>70%

Curated test queries

Historical variant match

>60%

Curated test queries

Typo tolerance

>90% for 1-2 char errors

Synthetic typo test set

14.2.2. User Satisfaction

Metric

Target

Measurement Method

Search success rate

>90%

“No results” rate reduction

Click-through rate

Improvement vs baseline

Analytics tracking

User feedback score

>4/5

Survey responses

14.3. Research Impact

14.3.1. Data Contribution

Deliverable

Target

Trained Siamese BiLSTM model

Open-source release

Training data (triplets)

Publicly available

Processing pipeline

Documented and reproducible

Evaluation test set

Published for benchmarking

14.3.2. Scholarly Output

Deliverable

Target

Methodology paper

Peer-reviewed publication

Technical documentation

Comprehensive and maintained

Workshop/tutorial

Conference presentation

14.4. Acceptance Criteria by Phase

14.4.1. Phase 2: Core Index Population

  • All authority sources ingested

  • Document counts match expectations (±1%)

  • Sample queries return expected results

  • Snapshot created and verified

14.4.2. Phase 4: Embedding Generation

  • BiLSTM model achieves recall@10 >80% on validation set

  • All toponyms have embeddings

  • kNN search returns results in <100ms (p95)

  • Vector search quality exceeds text-only baseline

14.4.3. Phase 6: Production Rollout

  • All technical metrics meet targets

  • User evaluation scores >4/5

  • Documentation complete

  • Runbooks tested and verified