Triple
T28368682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Township of the Second Class (Pennsylvania local government classification) |
E718563
|
entity |
| Predicate | typicalAreaType |
P6822
|
FINISHED |
| Object | rural areas |
—
|
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 areas | Statement: [Township of the Second Class (Pennsylvania local government classification), typicalAreaType, rural areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAreaType Context triple: [Township of the Second Class (Pennsylvania local government classification), typicalAreaType, rural areas]
-
A.
typicalRegionType
Indicates that a region is of a characteristic or commonly occurring type for a given context or entity.
-
B.
typeOfAreaRepresented
Indicates that one entity specifies the kind or category of area that another entity represents.
-
C.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
typicalZones
Indicates that certain spatial or contextual areas are characteristic or commonly associated with a given entity or situation.
-
E.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
- 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_69eff6ed5af48190be4e0adf298223e0 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_6a008e29f76881908e656dbbd7fceea3 |
completed | May 10, 2026, 1:54 p.m. |
| PD | Predicate disambiguation | batch_6a008dc01b308190bc26e69814692f82 |
completed | May 10, 2026, 1:53 p.m. |
Created at: April 28, 2026, 12:57 a.m.