Triple
T2321056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEP 572 |
E51179
|
entity |
| Predicate | examplePattern |
P8034
|
FINISHED |
| Object | while (line := file.readline()) != "": ... |
—
|
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: while (line := file.readline()) != "": ... | Statement: [PEP 572, examplePattern, while (line := file.readline()) != "": ...]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: examplePattern Context triple: [PEP 572, examplePattern, while (line := file.readline()) != "": ...]
-
A.
famousPattern
Indicates that one entity is widely recognized or renowned for a particular style, design, or recurring configuration associated with it.
-
B.
pattern
chosen
Indicates that one entity exhibits, follows, or is characterized by a particular recurring form, structure, or arrangement associated with another entity.
-
C.
notationPattern
Indicates a recurring way in which something is symbolically represented or written, such as a consistent style or structure of notation used for an entity or concept.
-
D.
usagePattern
Indicates how something is typically used or the recurring manner in which it is employed or consumed.
-
E.
kitPattern
Indicates the design or visual pattern featured on a team's kit or uniform.
- F. None of above.
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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.