Triple
T6607106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Can Tho municipality |
E149144
|
entity |
| Predicate | hasUrbanDistrictCount |
P72405
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Can Tho municipality, hasUrbanDistrictCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanDistrictCount Context triple: [Can Tho municipality, hasUrbanDistrictCount, 5]
-
A.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
-
B.
isUrbanDistrict
Indicates that a given district is classified as an urban administrative or residential area rather than a rural one.
-
C.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
-
D.
isUrbanCounty
Indicates that a county is classified as urban, typically based on population density, development level, or similar urbanization criteria.
-
E.
hasUrbanAreaApprox
Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
- F. None of above. chosen
Provenance (4 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_69c687eaa7508190bb58ce2aa02039b3 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cf3796d08190a26e988386089447 |
completed | March 27, 2026, 6:40 p.m. |
| PD | Predicate disambiguation | batch_69c6acfed25481909cac74c84a9fe088 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6cf3683d08190b19e2aad30f2800f |
completed | March 27, 2026, 6:40 p.m. |
Created at: March 27, 2026, 1:57 p.m.