Triple
T14950332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawit |
E372774
|
entity |
| Predicate | hasBarangaySubdivision |
P54409
|
FINISHED |
| Object | urban barangays |
—
|
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: urban barangays | Statement: [Kawit, hasBarangaySubdivision, urban barangays]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBarangaySubdivision Context triple: [Kawit, hasBarangaySubdivision, urban barangays]
-
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.
hasComponentBarangays
chosen
Indicates that an entity (typically a municipality, city, or similar administrative unit) is composed of or includes specific barangays as its subunits.
-
D.
hasIslandBarangays
Indicates that a locality or administrative unit possesses barangays that are located on islands.
-
E.
hasNumberOfSubdistricts
Indicates the relationship specifying how many subdistricts are associated with a given entity.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68fae3c81909873b113bfcaca05 |
completed | April 15, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:39 a.m.