Triple
T5895139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sails.js |
E131082
|
entity |
| Predicate | supportsViewEngine |
P9412
|
FINISHED |
| Object | Handlebars (via adapter) |
E183388
|
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: Handlebars (via adapter) | Statement: [Sails.js, supportsViewEngine, Handlebars (via adapter)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Handlebars (via adapter) Context triple: [Sails.js, supportsViewEngine, Handlebars (via adapter)]
-
A.
Handlebars
chosen
Handlebars is a popular logic-less templating engine for JavaScript that enables clean, readable templates with embedded expressions for dynamic HTML generation.
-
B.
Haml
Haml is a whitespace-sensitive templating language for Ruby that provides a clean, indentation-based syntax for generating HTML.
-
C.
Hanami::View
Hanami::View is the presentation layer component of the Hanami Ruby web framework, responsible for rendering templates and encapsulating view logic.
-
D.
EJS
EJS (Embedded JavaScript) is a simple templating language that lets you generate HTML markup with plain JavaScript code.
-
E.
Underscore.js
Underscore.js is a popular JavaScript utility library that provides functional programming helpers for working with arrays, objects, and other data types.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c036f3364c81909353f62ca483f24f |
completed | March 22, 2026, 6:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b1558fa48190a6ecde69c1477863 |
completed | March 23, 2026, 3:19 a.m. |
Created at: March 22, 2026, 3:58 p.m.