Triple
T36457992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middle Atlantic division |
E898211
|
entity |
| Predicate | includesUrbanRuralMix |
P24917
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Middle Atlantic division, includesUrbanRuralMix, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesUrbanRuralMix Context triple: [Middle Atlantic division, includesUrbanRuralMix, yes]
-
A.
hasUrbanRuralMix
chosen
Indicates that something exhibits a combination or blend of both urban and rural characteristics or components.
-
B.
urbanRuralSplit
Indicates a division or distinction between urban and rural areas, conditions, or populations.
-
C.
isRuralOrUrban
Indicates whether an entity is classified as being in a rural area or an urban area.
-
D.
hasUrbanVillages
Indicates that an entity contains or includes one or more designated urban villages within its area or jurisdiction.
-
E.
urbanRuralRelation
Indicates a relationship that characterizes how urban and rural areas are connected, contrasted, or interact with each other.
- 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_69f76e57f08481908593bd0bc34581c8 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:10 p.m.