Triple
T7403190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annette |
E170799
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Netty |
E426665
|
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: Netty | Statement: [Annette, hasDiminutive, Netty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Netty Context triple: [Annette, hasDiminutive, Netty]
-
A.
NIO
NIO is a Chinese electric vehicle manufacturer known for its premium smart EVs and innovative battery-swapping technology.
-
B.
Eclipse Vert.x
Eclipse Vert.x is a high-performance, event-driven application framework for the Java Virtual Machine designed for building reactive, scalable, and polyglot networked applications.
-
C.
Jetty
Jetty is a lightweight, embeddable Java-based web server and servlet container widely used for hosting web applications and supporting modern web protocols.
-
D.
Jetty
Jetty is a celebrated painting by contemporary artist Peter Doig, known for its atmospheric, dreamlike depiction of a solitary figure on a lakeside structure.
-
E.
ZeroMQ
chosen
ZeroMQ is a high-performance asynchronous messaging library that provides lightweight, flexible sockets for building scalable distributed and concurrent applications.
- 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26ea27c8190a55e0e0314b463d8 |
completed | March 27, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81110d7648190a8938db7061be454 |
completed | March 28, 2026, 5:34 p.m. |
Created at: March 27, 2026, 3:10 p.m.