Triple
T7898371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supertest |
E183387
|
entity |
| Predicate | usedWith |
P4791
|
FINISHED |
| Object | Fastify |
E554817
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Fastify | Statement: [Supertest, usedWith, Fastify]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fastify Context triple: [Supertest, usedWith, Fastify]
-
A.
Fastify
chosen
Fastify is a high-performance, low-overhead web framework for Node.js designed for building fast and scalable HTTP APIs.
-
B.
FastAPI
FastAPI is a modern, high-performance Python framework for building APIs with automatic interactive documentation and type hint–driven validation.
-
C.
Vite
Vite is a modern, lightning-fast frontend build tool and development server that leverages native ES modules and optimized bundling for frameworks like Vue and React.
-
D.
Uvicorn
Uvicorn is a high-performance, ASGI-compatible web server implementation for Python, commonly used to run modern async frameworks and applications.
-
E.
FeathersJS
FeathersJS is a lightweight, real-time microservices framework for Node.js that simplifies building REST and WebSocket APIs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a2ae5048190a6824d34b582c366 |
completed | March 31, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bb719a08190a0545a361f559bf7 |
completed | March 31, 2026, 5:29 a.m. |
Created at: March 30, 2026, 5:01 p.m.