Triple
T18476162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barangay Caniogan |
E451437
|
entity |
| Predicate | isUrbanBarangay |
P131788
|
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, isUrbanBarangay, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanBarangay Context triple: [Barangay Caniogan, isUrbanBarangay, true]
-
A.
hasUrbanBarangays
Indicates that a place or administrative unit possesses one or more barangays classified as urban.
-
B.
isHighlyUrbanizedCityBarangay
Indicates that a barangay is located within a city and exhibits a high degree of urban development and urban characteristics.
-
C.
hasNumberOfBarangays
Indicates the total count of barangays associated with a given administrative unit or locality.
-
D.
barangay
Indicates that an entity is associated with, located in, or falls under the jurisdiction of a specific barangay (the smallest local administrative division).
-
E.
isUrbanLocalGovernmentUnitOf
Indicates that one entity functions as the urban local government authority responsible for administering the other entity.
- 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.