Triple
T11216064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEP 484 |
E265441
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Pyright |
E911256
|
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: Pyright | Statement: [PEP 484, influenced, Pyright]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pyright Context triple: [PEP 484, influenced, Pyright]
-
A.
Pyright
chosen
Pyright is a fast, static type checker for Python that provides comprehensive type analysis, including support for advanced features like generic types.
-
B.
Repyt
Repyt is an ancient Egyptian lioness goddess primarily worshipped at Akhmim, associated with protection and sometimes linked to solar and warlike aspects.
-
C.
Pyr
Pyr is a science fiction and fantasy publishing imprint known for releasing speculative fiction titles under the Prometheus Books umbrella.
-
D.
PyPy
PyPy is a high-performance alternative Python interpreter featuring a Just-In-Time (JIT) compiler designed to significantly speed up the execution of Python programs.
-
E.
Pym
Pym is an English surname most notably associated with John Pym, a leading parliamentary figure in the early stages of the English Civil War.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8e8eef48190932a85784ce15c86 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad1c57908190a5c65ea4738722e3 |
completed | April 19, 2026, 10:23 a.m. |
Created at: April 8, 2026, 9:30 p.m.