Triple
T8582838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawar alphabet |
E203224
|
entity |
| Predicate | supportsDigraphs |
P54131
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hawar alphabet, supportsDigraphs, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDigraphs Context triple: [Hawar alphabet, supportsDigraphs, yes]
-
A.
usesDigraph
Indicates that one entity employs or represents information using a directed graph structure, where relationships have a specified direction.
-
B.
hasDigraph
chosen
Indicates that one entity is associated with or represented by a specific digraph (a two-character sequence treated as a single unit).
-
C.
usesTrigraph
Indicates that one entity employs or incorporates a trigraph (a three-character sequence representing a single unit, such as a sound or symbol) in relation to another entity or context.
-
D.
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.
-
E.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written 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_69ca8329bb7c8190a63c643730839103 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbeb1d0edc8190b4495935275252f3 |
completed | March 31, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69cbd11b13108190b07f8f161425a585 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:22 p.m.