Triple
T10828066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python visual identity |
E255542
|
entity |
| Predicate | governsUseOf |
P760
|
FINISHED |
| Object | Python logo |
E255543
|
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: Python logo | Statement: [Python visual identity, governsUseOf, Python logo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Python logo Context triple: [Python visual identity, governsUseOf, Python logo]
-
A.
Python logo with two snakes
chosen
The "Python logo with two snakes" is the iconic emblem of the Python programming language, featuring two interlocking stylized snake shapes that form a distinctive, blocky symbol.
-
B.
Pythonidae
Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
-
C.
Python
Python is a monstrous serpent or dragon from Greek mythology, best known for being slain by the god Apollo at Delphi.
-
D.
Python
Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
-
E.
Python visual identity
Python visual identity is the cohesive set of visual design elements—such as logos, colors, and typography—that represent and brand the Python programming language across media and platforms.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d734d2b9f88190b79a7b168d7836c8 |
completed | April 9, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb1096cbc81908f3eda562c2da042 |
completed | April 14, 2026, 9:26 p.m. |
Created at: April 8, 2026, 9:19 p.m.