Triple
T441054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British English |
E10113
|
entity |
| Predicate | contrastsWithVocabulary |
P12379
|
FINISHED |
| Object | truck |
—
|
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: truck | Statement: [British English, contrastsWithVocabulary, truck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastsWithVocabulary Context triple: [British English, contrastsWithVocabulary, truck]
-
A.
oftenContrastedWith
Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
-
B.
hasDistinctVocabulary
chosen
Indicates that one entity’s vocabulary is different or distinguishable from that of another entity.
-
C.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
D.
lexicalChange
Indicates a relationship where one linguistic form is replaced, modified, or evolves into another form over time or across language varieties.
-
E.
genreContrast
Indicates a relationship where two or more works are compared or juxtaposed based on differences between their genres.
- 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.