Triple
T3402749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umbundu |
E71693
|
entity |
| Predicate | hasOrthographyBasedOn |
P9874
|
FINISHED |
| Object | Portuguese-based Latin alphabet conventions |
—
|
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: Portuguese-based Latin alphabet conventions | Statement: [Umbundu, hasOrthographyBasedOn, Portuguese-based Latin alphabet conventions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrthographyBasedOn Context triple: [Umbundu, hasOrthographyBasedOn, Portuguese-based Latin alphabet conventions]
-
A.
hasOfficialOrthography
Indicates that an entity has a formally recognized and standardized system for writing its language or name.
-
B.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
C.
hasStandardPronunciationBasedOn
Indicates that one entity’s standard or canonical pronunciation is determined or derived from another entity’s pronunciation.
-
D.
hasStandardOrthographySince
Indicates that a language or writing system has used a particular standardized orthography starting from a specified point in time.
-
E.
writingSystemDevelopedFrom
chosen
Indicates that one writing system originated, evolved, or was derived from another earlier writing system.
- 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_69ad85aac4808190a092c9cc8911f584 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb8e78ec8819089417666dc29f412 |
completed | March 8, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69adadfa73ac8190a163f93e88d217f8 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.