Triple
T25634596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caddagat |
E642663
|
entity |
| Predicate | contrastsWithSetting |
P123206
|
FINISHED |
| Object | Sybylla Melvyn’s parents’ struggling bush farm |
—
|
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: Sybylla Melvyn’s parents’ struggling bush farm | Statement: [Caddagat, contrastsWithSetting, Sybylla Melvyn’s parents’ struggling bush farm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastsWithSetting Context triple: [Caddagat, contrastsWithSetting, Sybylla Melvyn’s parents’ struggling bush farm]
-
A.
providesContrastWith
chosen
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
-
B.
initiallyContrastsWith
Indicates that one entity is first presented or perceived in opposition or contrast to another entity at the beginning of a sequence, process, or context.
-
C.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
-
D.
achievesContrast
Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
-
E.
dramaticContrastWith
Indicates that one entity is presented in a way that sharply emphasizes differences in tone, style, or impact when compared with another entity.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 21, 2026, 5:21 p.m.