Triple
T14796080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King County, Texas |
E347779
|
entity |
| Predicate | ruralUrbanStatus |
P60791
|
FINISHED |
| Object | rural county |
—
|
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 county | Statement: [King County, Texas, ruralUrbanStatus, rural county]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruralUrbanStatus Context triple: [King County, Texas, ruralUrbanStatus, rural county]
-
A.
isRuralOrUrban
chosen
Indicates whether an entity is classified as being in a rural area or an urban area.
-
B.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
C.
locatedInUrbanizationType
Indicates that one entity is situated within, or belongs to, a specific type or category of urbanized area (e.g., city, suburb, metropolitan zone).
-
D.
isInRuralAreaOf
Indicates that one entity is located within the rural area or countryside region associated with another entity.
-
E.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5fdd548190a2ee5e668c2b20b4 |
completed | April 14, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.