Triple
T6488917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Emsworth Acts for the Best |
E147983
|
entity |
| Predicate | featuresSettingType |
P32516
|
FINISHED |
| Object | country house |
—
|
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: country house | Statement: [Lord Emsworth Acts for the Best, featuresSettingType, country house]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSettingType Context triple: [Lord Emsworth Acts for the Best, featuresSettingType, country house]
-
A.
featuresSetting
chosen
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
B.
featureSet
Indicates that one entity is a collection or configuration of features associated with or applied to another entity.
-
C.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
D.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
-
E.
featuresService
Indicates that one entity provides, includes, or offers a particular service as a notable characteristic or component.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a97fff88190b6f993c14df62649 |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:52 p.m.