Triple
T17919015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barangay Sagad |
E448014
|
entity |
| Predicate | isHighlyUrbanizedCityBarangay |
P129320
|
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 Sagad, isHighlyUrbanizedCityBarangay, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isHighlyUrbanizedCityBarangay Context triple: [Barangay Sagad, isHighlyUrbanizedCityBarangay, true]
-
A.
hasUrbanBarangays
Indicates that a place or administrative unit possesses one or more barangays classified as urban.
-
B.
hasNumberOfBarangays
Indicates the total count of barangays associated with a given administrative unit or locality.
-
C.
isHighlyUrbanizedCityOf
Indicates that a city is characterized by a high degree of urban development and population density within the specified larger region or jurisdiction.
-
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.
hasNumberOfBarrios
Indicates the specific count of barrios (neighborhoods) associated with a given 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30844548190b7a43c2f093f35d7 |
completed | April 19, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
| PDg | Predicate description generation | batch_69e3db77df0c819084548168c62b398c |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:20 a.m.