Triple
T26183004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kepanjen |
E654738
|
entity |
| Predicate | isGrowingUrbanArea |
P37508
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kepanjen, isGrowingUrbanArea, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGrowingUrbanArea Context triple: [Kepanjen, isGrowingUrbanArea, true]
-
A.
isUrbanizing
chosen
Indicates a process in which an area or population becomes more urban in character, typically through increased development, infrastructure, and concentration of people and activities.
-
B.
hasUrbanGrowthCharacteristic
Indicates that an entity exhibits a particular quality, pattern, or feature related to urban growth or expansion.
-
C.
significantUrbanArea
Indicates that a location is classified as a major or important urban center within a broader geographic or administrative context.
-
D.
isUrbanizedAround
Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
-
E.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
- 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_69ee5b469bc081908fe486453fdad810 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60c71dfb48190a3f0ab63ecadbdfa |
completed | May 2, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69f5b007ec1c819092e2c3605933f60b |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 8:41 p.m.