Triple
T13849777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shottisham |
E332902
|
entity |
| Predicate | hasTraditionalCountrysideCharacter |
P85002
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Shottisham, hasTraditionalCountrysideCharacter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalCountrysideCharacter Context triple: [Shottisham, hasTraditionalCountrysideCharacter, true]
-
A.
hasTraditionalCotswoldCharacter
Indicates that something exhibits the typical aesthetic, architectural, or cultural qualities associated with traditional Cotswold style.
-
B.
hasRuralLandscapeType
chosen
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
-
C.
traditionallyHouses
Indicates that one entity has historically or customarily served as the location or container for another entity.
-
D.
hasTraditionalSettlementType
Indicates that an entity is associated with a specific traditional or historically established type of human settlement (e.g., village, town, hamlet).
-
E.
semiRuralCharacter
Indicates that a place or area has characteristics intermediate between rural and urban, combining elements of both environments.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02d8fb788190baef7537be2baecb |
completed | April 14, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69dbc8691b608190a25a7c70a366b170 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:14 p.m.