Triple
T377343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kannada |
E8600
|
entity |
| Predicate | hasWritingSystemSince |
P1436
|
FINISHED |
| Object | at least 5th century CE |
—
|
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: at least 5th century CE | Statement: [Kannada, hasWritingSystemSince, at least 5th century CE]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWritingSystemSince Context triple: [Kannada, hasWritingSystemSince, at least 5th century CE]
-
A.
writingSystemDevelopedFrom
Indicates that one writing system originated, evolved, or was derived from another earlier writing system.
-
B.
hasStandardOrthographySince
Indicates that a language or writing system has used a particular standardized orthography starting from a specified point in time.
-
C.
hasWritingTraditionSince
chosen
Indicates that a writing tradition has been present or established for an entity starting from a specified point in time.
-
D.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
-
E.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec1804108190a1e94526b71289ea |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96351cc8190a55adf95f8c27e9e |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.