Triple
T18002175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barangay Kapitolyo |
E430653
|
entity |
| Predicate | hasTypeOfEstablishment |
P68868
|
FINISHED |
| Object | eateries |
—
|
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: eateries | Statement: [Barangay Kapitolyo, hasTypeOfEstablishment, eateries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfEstablishment Context triple: [Barangay Kapitolyo, hasTypeOfEstablishment, eateries]
-
A.
hasEstablishment
Indicates that one entity possesses, operates, or is associated with a particular establishment (such as a business, facility, or institution).
-
B.
operatedEstablishmentIn
Indicates that an entity ran or managed an establishment located within a specified place or jurisdiction.
-
C.
hasTypeOfBusinesses
chosen
Indicates that an entity is associated with or contains specific categories or kinds of businesses.
-
D.
hasTypeOfOrganization
Indicates that an entity is classified as belonging to a particular type or category of organization.
-
E.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b3e9498c8190bdfa7a53b0c0d8db |
completed | April 19, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.