Triple
T441043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British English |
E10113
|
entity |
| Predicate | contrastsWithSpelling |
P11289
|
FINISHED |
| Object | color |
—
|
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: color | Statement: [British English, contrastsWithSpelling, color]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastsWithSpelling Context triple: [British English, contrastsWithSpelling, color]
-
A.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
B.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
C.
oftenContrastedWith
chosen
Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
-
D.
hasRomanizationContrast
Indicates that there is a meaningful difference between two or more romanized representations of the same original form.
-
E.
hasPhonemicContrast
Indicates that two or more speech sounds are distinguished in a language by differences that change word meaning.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef2af84881909635ebbbb3465b1b |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddcf50c8190bfa0d1f8ee9f604a |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.