Triple
T11944344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yorketown |
E284255
|
entity |
| Predicate | isRuralServiceTownFor |
P16346
|
FINISHED |
| Object | surrounding farming districts |
—
|
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: surrounding farming districts | Statement: [Yorketown, isRuralServiceTownFor, surrounding farming districts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRuralServiceTownFor Context triple: [Yorketown, isRuralServiceTownFor, surrounding farming districts]
-
A.
isRuralServiceTown
chosen
Indicates that a town functions primarily as a service and support center for surrounding rural or agricultural areas.
-
B.
hasRuralServiceTown
Indicates that a rural area or region is associated with, and typically receives services from, a specific town that functions as its service center.
-
C.
isInRuralAreaOf
Indicates that one entity is located within the rural area or countryside region associated with another entity.
-
D.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
E.
isRuralRegion
Indicates that a region is classified as rural, typically characterized by low population density and limited urban development.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9034444488190925a6fa6c856ed08 |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.