clossers/didi-lot1-ai
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Livrare LOT 1 - Didi

Browse source
This commit is contained in:
Dezvoltari Evotech 2026-06-25 14:13:25 -07:00
commit 5380c3fc63
990 changed files with 133308 additions and 0 deletions
Download patch file Download diff file Expand all files Collapse all files

63
artefacte_lot1/output_teste/web/gather_results.md Normal file
View file

@ -0,0 +1,63 @@
# Web API Gather Results - NER & Fact-Checking Research
Generated: 2026-01-30
---
## Query 1: MultiNERD Entity Types
**Claim:** `MultiNERD entity types list NER categories person organization location date time money percentage fact-checking`
**Execution Time:** 5203ms
### URLs Accessed
- [Named-entity recognition - Wikipedia](https://en.wikipedia.org/wiki/Named-entity_recognition)
- [Gold standard, multi-genre dataset for named entity recognition and linking | Scientific Data](https://www.nature.com/articles/s41597-025-05274-4)
- [Named Entity Recognition (NER): Ultimate Guide | Encord](https://encord.com/blog/named-entity-recognition/)
- [A Comprehensive Guide to Named Entity Recognition](https://www.turing.com/kb/a-comprehensive-guide-to-named-entity-recognition)
- [Entity categories recognized by Named Entity Recognition in Azure](https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/concepts/named-entity-categories)
---
## Query 2: Fact-Checking Methodology
**Claim:** `fact-checking entity extraction named entity recognition claim verification ClaimBuster Full Fact methodology 2024`
**Execution Time:** 9698ms
### URLs Accessed
- [arxiv.org PDF 1809.08193](https://arxiv.org/pdf/1809.08193)
- [Claim Extraction for Fact-Checking: Data, Models, and Automated Metrics](https://arxiv.org/html/2502.04955v1)
- [Facilitating automated fact-checking: a machine learning based weighted ensemble technique for claim detection](https://link.springer.com/article/10.1007/s42452-024-06444-6)
- [Document-level Claim Extraction and Decontextualisation for Fact-Checking](https://arxiv.org/html/2406.03239v2)
- [An Entity-based Claim Extraction Pipeline for Real-world Biomedical Fact-checking](https://arxiv.org/abs/2304.05268)
---
## Query 3: NER Query Generation for Fact-Checking
**Claim:** `named entity recognition query generation fact-checking entity types person organization location date event claim verification search query templates`
**Execution Time:** 3485ms
### URLs Accessed
- [Tools for Named Entity Recognition | CLARIN ERIC](https://www.clarin.eu/resource-families/tools-named-entity-recognition)
- [Named-entity recognition - Wikipedia](https://en.wikipedia.org/wiki/Named-entity_recognition)
- [Named Entity Recognition - GeeksforGeeks](https://www.geeksforgeeks.org/nlp/named-entity-recognition/)
- [Named Entity Recognition | Yext](https://www.yext.com/platform/features/named-entity-recognition)
- [Named Entity Recognition on Search Engine Queries with Python - Stack Overflow](https://stackoverflow.com/questions/78151241/named-entity-recognition-on-search-engine-queries-with-python)
---
## Summary
| Query | Evidence URLs | Execution Time |
|-------|---------------|----------------|
| 1 - MultiNERD Entity Types | 5 | 5.2s |
| 2 - Fact-Checking Methodology | 5 | 9.7s |
| 3 - NER Query Generation | 5 | 3.5s |
**Total URLs:** 15