Triple
T1159988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ECMAScript |
E24470
|
entity |
| Predicate | influences |
P9
|
FINISHED |
| Object | CoffeeScript |
E17652
|
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: CoffeeScript | Statement: [ECMAScript, influences, CoffeeScript]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CoffeeScript Context triple: [ECMAScript, influences, CoffeeScript]
-
A.
CoffeeScript
chosen
CoffeeScript is a programming language that compiles to JavaScript, offering a more concise, Python- and Ruby-like syntax for writing web application code.
-
B.
Elixir
Elixir is a functional, concurrent programming language built on the Erlang VM, known for its scalability, fault tolerance, and expressive syntax.
-
C.
Ruby on Rails
Ruby on Rails is a popular open-source web application framework that emphasizes convention over configuration and rapid development for building database-backed applications.
-
D.
Ruby
Ruby is a dynamic, object-oriented programming language known for its elegant syntax and its use in the Ruby on Rails web framework.
-
E.
Ruby
Ruby is the titular woman in the country song "Ruby, Don’t Take Your Love to Town," known for contemplating leaving her disabled veteran husband for another man.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcaf3a9081908bad2eba74dffbc1 |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac5ebbf80881909010e1e1e59212d4 |
completed | March 7, 2026, 5:22 p.m. |
Created at: March 1, 2026, 7:45 p.m.