Triple
T4276135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CircuitPython |
E97050
|
entity |
| Predicate | typicalEntryFile |
P55132
|
FINISHED |
| Object | code.py |
—
|
LITERAL 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: code.py | Statement: [CircuitPython, typicalEntryFile, code.py]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEntryFile Context triple: [CircuitPython, typicalEntryFile, code.py]
-
A.
typicalEntryType
Indicates the usual or standard category or kind of entry associated with something.
-
B.
typicalEntryRoute
Indicates the usual or most common path or method by which something is entered or accessed.
-
C.
entryPointFor
Indicates that one entity serves as the access or starting location through which another entity is entered, initiated, or reached.
-
D.
typicalBase
Indicates that one entity serves as the standard or most representative base or foundation for another entity in typical or common cases.
-
E.
typicalKey
Indicates that the referenced key is the standard or most commonly used key associated with an entity or context.
- F. None of above. chosen
Provenance (4 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501d677481909e7416a1d2b0008c |
completed | March 12, 2026, 11:45 p.m. |
| PD | Predicate disambiguation | batch_69b347faa45481908c19c29fb906dc92 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:07 p.m.