Triple
T19741828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zouping |
E474141
|
entity |
| Predicate | hasLevelOfUrbanization |
P9969
|
FINISHED |
| Object | highly industrialized |
—
|
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: highly industrialized | Statement: [Zouping, hasLevelOfUrbanization, highly industrialized]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLevelOfUrbanization Context triple: [Zouping, hasLevelOfUrbanization, highly industrialized]
-
A.
urbanizationLevel
chosen
Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
-
B.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
-
C.
isUrbanizedAround
Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
-
D.
hasUrbanClassification
Indicates that an entity is assigned a specific urban status or category within a defined classification system.
-
E.
hasUrbanPopulationIn
Indicates that an entity has a specified urban population within a particular geographic area or administrative unit.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65162382081909bd5a251d7da7f75 |
completed | April 20, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.