Triple
T4325742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | uWSGI |
E96630
|
entity |
| Predicate | supportsLanguage |
P2177
|
FINISHED |
| Object | Clojure |
E308600
|
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: Clojure | Statement: [uWSGI, supportsLanguage, Clojure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clojure Context triple: [uWSGI, supportsLanguage, Clojure]
-
A.
Clojure
chosen
Clojure is a modern, functional, and dynamic dialect of Lisp that runs on the Java Virtual Machine and emphasizes immutability and concurrent programming.
-
B.
Lisp programming language
Lisp is a pioneering high-level programming language, especially influential in artificial intelligence research and known for its symbolic processing and distinctive parenthesized syntax.
-
C.
Racket
Racket is a modern, multi-paradigm programming language in the Lisp/Scheme family, designed for language-oriented programming, scripting, and education.
-
D.
Common Lisp
Common Lisp is a powerful, multi-paradigm dialect of the Lisp programming language standardised in the 1980s, known for its rich macro system, dynamic typing, and suitability for large-scale, extensible software systems.
-
E.
Chez Scheme
Chez Scheme is a high-performance, optimizing implementation of the Scheme programming language widely used for both research and production systems.
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3513020f481909ff2fec3934f3002 |
completed | March 12, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d09861a4819086a88bb42a8ea2e4 |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:13 p.m.