Triple
T3987625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White |
E86909
|
entity |
| Predicate | spellingStability |
P53680
|
FINISHED |
| Object | relatively stable modern spelling |
—
|
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: relatively stable modern spelling | Statement: [White, spellingStability, relatively stable modern spelling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spellingStability Context triple: [White, spellingStability, relatively stable modern spelling]
-
A.
effectOnSpelling
Indicates a relationship where one factor influences or alters the way something is spelled.
-
B.
sharesSpellingWith
Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
-
C.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
D.
usesStandardOrthographyOf
Indicates that one entity writes or represents language according to the standard orthographic system defined for another entity.
-
E.
languageReform
Indicates efforts or actions aimed at changing, standardizing, or improving aspects of a language, such as its spelling, grammar, or usage rules.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefb7f92348190ae35f1d75b0b5d4f |
completed | March 9, 2026, 4:55 p.m. |
Created at: March 9, 2026, 3:33 p.m.