Triple
T192106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JavaScript |
E3742
|
entity |
| Predicate | runsOn |
P23
|
FINISHED |
| Object |
Node.js
Node.js is an open-source, cross-platform runtime environment that allows developers to execute JavaScript code on the server side.
|
E24471
|
NE FINISHED |
How this triple was built (4 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: Node.js | Statement: [JavaScript, runsOn, Node.js]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Node.js Context triple: [JavaScript, runsOn, Node.js]
-
A.
JavaScript
JavaScript is a high-level, dynamic programming language primarily used to create interactive and dynamic content on web pages.
-
B.
CoffeeScript
CoffeeScript is a programming language that compiles to JavaScript, offering a more concise, Python- and Ruby-like syntax for writing web application code.
-
C.
TypeScript programming language
TypeScript is a statically typed superset of JavaScript that adds optional type annotations and modern language features to improve large-scale application development.
-
D.
Julia
Julia is a high-level, high-performance programming language designed for numerical computing, data science, and scientific research, combining the ease of dynamic languages with the speed of compiled languages.
-
E.
Rust
Rust is a modern systems programming language focused on memory safety, concurrency, and performance without a garbage collector.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Node.js Triple: [JavaScript, runsOn, Node.js]
Generated description
Node.js is an open-source, cross-platform runtime environment that allows developers to execute JavaScript code on the server side.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Node.js Target entity description: Node.js is an open-source, cross-platform runtime environment that allows developers to execute JavaScript code on the server side.
-
A.
JavaScript
JavaScript is a high-level, dynamic programming language primarily used to create interactive and dynamic content on web pages.
-
B.
CoffeeScript
CoffeeScript is a programming language that compiles to JavaScript, offering a more concise, Python- and Ruby-like syntax for writing web application code.
-
C.
TypeScript programming language
TypeScript is a statically typed superset of JavaScript that adds optional type annotations and modern language features to improve large-scale application development.
-
D.
Julia
Julia is a high-level, high-performance programming language designed for numerical computing, data science, and scientific research, combining the ease of dynamic languages with the speed of compiled languages.
-
E.
Rust
Rust is a modern systems programming language focused on memory safety, concurrency, and performance without a garbage collector.
- F. None of above. chosen
Provenance (5 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a259669ba08190a5be1d2e10e70b27 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a30cc6bfdc819091478e5102a3d64f |
completed | Feb. 28, 2026, 3:41 p.m. |
| NEDg | Description generation | batch_69a30d5e9d788190b69c964001c8b7ce |
completed | Feb. 28, 2026, 3:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a30dc3fe5081909b90a55d8e0451d6 |
completed | Feb. 28, 2026, 3:46 p.m. |
Created at: Feb. 28, 2026, 2:41 a.m.