Triple
T8254897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherokee syllabary |
E193047
|
entity |
| Predicate | timeToWidespreadUse |
P21730
|
FINISHED |
| Object | within a few years of introduction |
—
|
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: within a few years of introduction | Statement: [Cherokee syllabary, timeToWidespreadUse, within a few years of introduction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeToWidespreadUse Context triple: [Cherokee syllabary, timeToWidespreadUse, within a few years of introduction]
-
A.
marketAdoption
Indicates the extent to which a product, service, or innovation has been accepted and used by its target market or customer base.
-
B.
popularizedAfter
Indicates that one entity became widely known, accepted, or influential only after another specified entity had already gained popularity.
-
C.
decadeOfPopularization
chosen
Indicates the decade during which something became widely known, used, or popular.
-
D.
isWidelyUsed
Indicates that something is commonly or extensively utilized across many contexts, users, or situations.
-
E.
firstWidelyUsedFor
Indicates that something was the earliest instance to be broadly adopted or commonly used for a particular purpose or application.
- 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78f8eccc8190b43204bf2f8defc1 |
completed | March 31, 2026, 7:34 a.m. |
| PD | Predicate disambiguation | batch_69cb36b6d5548190b665a6cce14c69f7 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:48 p.m.