Triple
T24266716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samoan alphabet |
E604857
|
entity |
| Predicate | macronUsedFor |
P93847
|
FINISHED |
| Object | long vowels |
—
|
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: long vowels | Statement: [Samoan alphabet, macronUsedFor, long vowels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: macronUsedFor Context triple: [Samoan alphabet, macronUsedFor, long vowels]
-
A.
macrolanguageWith
Indicates that one language is classified as a macrolanguage that encompasses or groups together another, more specific language variety.
-
B.
hasMacrolanguage
Indicates that a language is part of, or grouped under, a broader macrolanguage that encompasses multiple closely related language varieties.
-
C.
hasMacronRomanization
chosen
Indicates that an entity is associated with a Romanized form of text that uses macrons to mark long vowels.
-
D.
macrolanguage
Indicates that a language is classified as a macrolanguage encompassing multiple closely related individual languages or varieties.
-
E.
accentedFormOf
Indicates that one linguistic form is an accented or diacritically marked variant of another, more basic form.
- 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_69e29544c29c8190b023606eafe5d36a |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28c6bfe68819084ec59235ae58ff1 |
completed | April 29, 2026, 10:55 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:06 a.m.