Triple
T8964400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayog |
E214089
|
entity |
| Predicate | localGovernmentUnitType |
P32279
|
FINISHED |
| Object | 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: barangay | Statement: [Bayog, localGovernmentUnitType, barangay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localGovernmentUnitType Context triple: [Bayog, localGovernmentUnitType, barangay]
-
A.
localGovernmentAreaType
Indicates the specific classification or category of a local government area within an administrative or governmental hierarchy.
-
B.
governmentalUnitType
chosen
Indicates the specific category or classification of a governmental unit (such as federal, state, municipal, or other administrative level) that an entity belongs to.
-
C.
localGovernmentAreaOf
Indicates that one entity is the local government area within whose jurisdiction or administrative boundaries the other entity is located.
-
D.
governmentalUnit
Indicates that one entity functions as a governmental or administrative unit in relation to another entity.
-
E.
municipalWardType
Indicates the specific category or classification of a municipal ward within a local government or administrative structure.
- 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_69ca839cd6008190a1546a701a56710c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc674c4be8819090d46aba8ab40af3 |
completed | April 1, 2026, 12:31 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed74d288190b712d739805579dc |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:01 p.m.