Triple
T4555327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lumen |
E120464
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Laravel |
E120464
|
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: Laravel | Statement: [Lumen, basedOn, Laravel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laravel Context triple: [Lumen, basedOn, Laravel]
-
A.
Laravel
chosen
Laravel is a popular open-source PHP web application framework known for its elegant syntax, robust tooling, and support for rapid application development.
-
B.
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.
-
C.
Slim Framework
Slim Framework is a lightweight PHP micro-framework designed for building simple yet powerful web applications and APIs with minimal overhead.
-
D.
CakePHP
CakePHP is an open-source rapid development web framework for PHP that follows the MVC pattern and emphasizes convention over configuration to streamline building web applications.
-
E.
Quasar Framework
Quasar Framework is a high-performance, Vue.js-based UI framework for building responsive web, mobile, and desktop applications from a single codebase.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd5813af948190b10b02dadf6496bf |
completed | March 20, 2026, 2:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdc57d59f88190857cbda79caf3c38 |
completed | March 20, 2026, 10:09 p.m. |
Created at: March 20, 2026, 1:09 p.m.