Triple
T18476147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barangay Caniogan |
E451437
|
entity |
| Predicate | isInHighlyUrbanizedCity |
P131787
|
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: [Barangay Caniogan, isInHighlyUrbanizedCity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInHighlyUrbanizedCity Context triple: [Barangay Caniogan, isInHighlyUrbanizedCity, true]
-
A.
isHighlyUrbanizedCityOf
Indicates that a city is characterized by a high degree of urban development and population density within the specified larger region or jurisdiction.
-
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.
isUrbanZoneFor
Indicates that a given area functions as an urban zone designated for a particular entity or purpose.
-
E.
isUrbanDistrict
Indicates that a given district is classified as an urban administrative or residential area rather than a rural one.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53062f67881909620c4e8fc00eb7d |
completed | April 19, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69e469d671088190b619de96ea6f92ab |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2aa72c8190a40854a7a52081e2 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:35 a.m.