Triple
T5827131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vallader |
E129254
|
entity |
| Predicate | hasOrthographicConvention |
P67410
|
FINISHED |
| Object | use of ‹ch› for /k/ before front vowels |
—
|
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: use of ‹ch› for /k/ before front vowels | Statement: [Vallader, hasOrthographicConvention, use of ‹ch› for /k/ before front vowels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrthographicConvention Context triple: [Vallader, hasOrthographicConvention, use of ‹ch› for /k/ before front vowels]
-
A.
hasOrthographicReform
Indicates that an entity has undergone or is associated with a change or standardization in its writing system or spelling conventions.
-
B.
usesStandardOrthographyOf
Indicates that one entity writes or represents language according to the standard orthographic system defined for another entity.
-
C.
hasOfficialOrthography
Indicates that an entity has a formally recognized and standardized system for writing its language or name.
-
D.
orthographicVariant
Indicates that two written forms are different spellings or orthographic representations of the same linguistic item.
-
E.
hasStandardOrthographySince
Indicates that a language or writing system has used a particular standardized orthography starting from a specified point in time.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69c044a9c4f0819081b8c196932883f6 |
completed | March 22, 2026, 7:36 p.m. |
Created at: March 22, 2026, 3:53 p.m.