Triple
T1082592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North American English |
E23978
|
entity |
| Predicate | usesSpellingConvention |
P457
|
FINISHED |
| Object | American English 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: American English spelling | Statement: [North American English, usesSpellingConvention, American English spelling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSpellingConvention Context triple: [North American English, usesSpellingConvention, American English spelling]
-
A.
hasVariantSpelling
chosen
Indicates that one term is an alternative spelling form of another term.
-
B.
usesAlphabet
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
C.
effectOnSpelling
Indicates a relationship where one factor influences or alters the way something is spelled.
-
D.
usedInSpokenForm
Indicates that something (such as a word, name, or expression) is employed in spoken language or oral communication.
-
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.
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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95e56948190a1e92367ad7240b7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73f4310819086281f8ec67d1a32 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.