Triple
T250521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baybayin |
E5135
|
entity |
| Predicate | characterSetType |
P8572
|
FINISHED |
| Object | syllabic |
—
|
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: syllabic | Statement: [Baybayin, characterSetType, syllabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterSetType Context triple: [Baybayin, characterSetType, syllabic]
-
A.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
B.
codingSystemContext
Indicates the coding system or classification framework within which a given code, identifier, or value is defined and interpreted.
-
C.
UnicodeBlock
Indicates that a character belongs to a specific contiguous range of code points defined as a Unicode block.
-
D.
hasGlyphRepertoireSize
Indicates the number of distinct glyphs included in an entity’s glyph repertoire.
-
E.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d38aba8819081d0958eb60ce27e |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b665f8c8190aac6fcbba2a0eebb |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c036b54819090a101c4cbdbcff7 |
completed | Feb. 28, 2026, 3:07 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.