Triple
T34504461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bassa Vah |
E885843
|
entity |
| Predicate | hasOrthographicFunction |
P10346
|
FINISHED |
| Object | standardizing Bassa spelling |
—
|
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: standardizing Bassa spelling | Statement: [Bassa Vah, hasOrthographicFunction, standardizing Bassa spelling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrthographicFunction Context triple: [Bassa Vah, hasOrthographicFunction, standardizing Bassa spelling]
-
A.
hasOrthographicSpace
Indicates that there is a space character or spacing separation between the written forms of the related entities in orthographic representation.
-
B.
hasOrthographicPreference
Indicates that one entity prefers or selects a particular written or spelling form of another entity.
-
C.
hasOrthographicConvention
Indicates that there is a specific writing or spelling convention that governs how something is represented in written form.
-
D.
orthographicProperty
Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
-
E.
hasOrthographicReform
chosen
Indicates that an entity has undergone or is associated with a change or standardization in its writing system or spelling conventions.
- 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_69f349cc0220819081f154c6964f4dc2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe920a437081908d5174e8cf7a53a6 |
completed | May 9, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69fe919a9a6c8190acb4483f386e6db7 |
completed | May 9, 2026, 1:44 a.m. |
Created at: May 1, 2026, 2:01 a.m.