Triple
T7087712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Discord |
E165119
|
entity |
| Predicate | programmingLanguage |
P1592
|
FINISHED |
| Object | Elixir |
E96206
|
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: Elixir | Statement: [Discord, programmingLanguage, Elixir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elixir Context triple: [Discord, programmingLanguage, Elixir]
-
A.
Elixir
chosen
Elixir is a functional, concurrent programming language built on the Erlang VM, known for its scalability, fault tolerance, and expressive syntax.
-
B.
Erlang
Erlang is a functional, concurrent programming language designed for building highly scalable, fault-tolerant distributed systems, originally developed by Ericsson for telecom applications.
-
C.
Phoenix Framework
Phoenix Framework is an Elixir-based web development framework known for its high performance, real-time capabilities, and productive developer experience inspired by Ruby on Rails.
-
D.
Elm
Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
-
E.
Elm
Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e52d26f08190917e5e13b181bdae |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c794888abc8190ada2ae826449745a |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:41 p.m.