Triple
T35362627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | north-eastern Hubei |
E1021533
|
entity |
| Predicate | hasUrbanRuralPattern |
P24917
|
FINISHED |
| Object | mix of medium-sized cities and rural counties |
—
|
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: mix of medium-sized cities and rural counties | Statement: [north-eastern Hubei, hasUrbanRuralPattern, mix of medium-sized cities and rural counties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanRuralPattern Context triple: [north-eastern Hubei, hasUrbanRuralPattern, mix of medium-sized cities and rural counties]
-
A.
isRuralOrUrban
Indicates whether an entity is classified as being in a rural area or an urban area.
-
B.
hasUrbanRuralMix
chosen
Indicates that something exhibits a combination or blend of both urban and rural characteristics or components.
-
C.
hasUrbanVillages
Indicates that an entity contains or includes one or more designated urban villages within its area or jurisdiction.
-
D.
hasUrbanAreaCharacter
Indicates that something possesses qualities, features, or conditions typical of an urban area.
-
E.
hasUrbanSectionsIn
Indicates that an entity includes or contains sections that are classified as urban within a specified area or region.
- 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_69f76def44c881908a20e8008572eb44 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.