Triple
T8730018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borama script |
E207229
|
entity |
| Predicate | hasGlyphsFor |
P84314
|
FINISHED |
| Object | Somali consonants |
—
|
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: Somali consonants | Statement: [Borama script, hasGlyphsFor, Somali consonants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGlyphsFor Context triple: [Borama script, hasGlyphsFor, Somali consonants]
-
A.
hasGlyphRepertoireSize
Indicates the number of distinct glyphs included in an entity’s glyph repertoire.
-
B.
hasLigatures
Indicates that one writing system, font, or text includes combined character forms (ligatures) that join two or more individual glyphs into a single symbol.
-
C.
hasTypography
Indicates that one entity uses, is associated with, or is characterized by a particular typographic style, font, or text layout.
-
D.
hasApproximateNumberOfPictographs
Indicates that an entity is associated with a quantity of pictographs that is not exact but estimated or approximate.
-
E.
hasNumberOfBasicCharacters
Indicates the quantity of basic (non-accented or fundamental) characters associated with an entity.
- F. None of above. chosen
Provenance (4 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d26d280819085e15d4917c2b9a5 |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc489dd528819084ed5d88bd8bb3d6 |
completed | March 31, 2026, 10:20 p.m. |
Created at: March 30, 2026, 6:37 p.m.