Triple
T23235761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dishley, Leicestershire |
E581287
|
entity |
| Predicate | hasApproximateType |
P151480
|
FINISHED |
| Object | rural area |
—
|
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: rural area | Statement: [Dishley, Leicestershire, hasApproximateType, rural area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateType Context triple: [Dishley, Leicestershire, hasApproximateType, rural area]
-
A.
hasApparentType
Indicates that something is perceived or classified as being of a particular type based on its observable characteristics or context.
-
B.
hasGoodType
Indicates that an entity possesses a type or classification considered appropriate, valid, or of high quality according to some defined criteria.
-
C.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
D.
hasFaithfulType
Indicates that one entity has a corresponding type or classification that remains consistent, reliable, or invariant with respect to some underlying structure or mapping.
-
E.
hasStandardType
Indicates that something conforms to or is categorized under a defined standard classification or type.
- F. None of above. chosen
Provenance (4 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_69e2460556f88190be1744a84a84173f |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192e8c7548190b53434eeb2620a6e |
completed | April 29, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69effcdadec0819092ec1749ee453b4e |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:09 p.m.