Triple
T13918887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xibe script |
E334689
|
entity |
| Predicate | orthographicSystem |
P79216
|
FINISHED |
| Object | segmental alphabet |
—
|
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: segmental alphabet | Statement: [Xibe script, orthographicSystem, segmental alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orthographicSystem Context triple: [Xibe script, orthographicSystem, segmental alphabet]
-
A.
orthographicBasis
Indicates that one writing system, spelling convention, or script is used as the reference or foundation for the orthography of another.
-
B.
orthographicGoal
Indicates that one entity has the intended or target written/orthographic form of another entity.
-
C.
orthographicProperty
Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
-
D.
orthographicMedium
chosen
Indicates the writing system, script, or orthographic form through which something (such as a text, name, or expression) is represented.
-
E.
orthographicRole
Indicates the functional role that a written form or spelling plays within an orthographic system (e.g., as a letter, diacritic, punctuation mark, or other script element).
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de272753e48190bc609482635280ff |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.