Triple
T17974876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barangay Sumilang |
E449443
|
entity |
| Predicate | belongsToCityClass |
P121869
|
FINISHED |
| Object | highly urbanized city of Pasig |
—
|
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: highly urbanized city of Pasig | Statement: [Barangay Sumilang, belongsToCityClass, highly urbanized city of Pasig]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToCityClass Context triple: [Barangay Sumilang, belongsToCityClass, highly urbanized city of Pasig]
-
A.
belongsToCityType
chosen
Indicates that one entity is classified under, or associated with, a particular type or category of city.
-
B.
belongsToCityServedBy
Indicates that something is associated with or part of the city that is served by a particular service, facility, or infrastructure.
-
C.
belongsToUrbanZone
Indicates that something is located within, or is a part of, a designated urban zone or area.
-
D.
refersToCityWithAttribute
Indicates that one entity refers to a city that possesses a specified attribute or set of attributes.
-
E.
hasAssociatedCity
Indicates that one entity is linked or related to a specific city, typically as its location, base, or primary area of association.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1fe24808190baa11739f4d1095f |
completed | April 19, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:22 a.m.