Triple
T19031222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maharlika Village |
E465741
|
entity |
| Predicate | residentialAreaType |
P9064
|
FINISHED |
| Object | residential barangay |
—
|
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: residential barangay | Statement: [Maharlika Village, residentialAreaType, residential barangay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: residentialAreaType Context triple: [Maharlika Village, residentialAreaType, residential barangay]
-
A.
residenceType
Indicates the kind or category of dwelling or living arrangement associated with an entity.
-
B.
hasResidentialArea
chosen
Indicates that an entity includes, contains, or is associated with an area designated for people to live or reside.
-
C.
isResidential
Indicates that something is used or designated primarily for people to live in, rather than for commercial, industrial, or other non-living purposes.
-
D.
hasResidentialBuildingsType
Indicates that an entity is associated with a specific type or category of residential buildings.
-
E.
typeOfHouse
Indicates the specific category or kind of house associated with an entity (e.g., apartment, detached house, townhouse).
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d7404d748190bcb51692fb822fd4 |
completed | April 20, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.