Triple
T29517562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The University City of Cavite |
E748840
|
entity |
| Predicate | regionOfCityReferred |
P156664
|
FINISHED |
| Object | Calabarzon |
—
|
NE NERFINISHED |
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: Calabarzon | Statement: [The University City of Cavite, regionOfCityReferred, Calabarzon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfCityReferred Context triple: [The University City of Cavite, regionOfCityReferred, Calabarzon]
-
A.
regionOfCityReferenced
Indicates that a specific region or area within a city is being referenced or mentioned in relation to another entity or context.
-
B.
regionOfCity
Indicates that a specified area or district is a constituent part or subdivision of a particular city.
-
C.
regionOfTheReferredCity
chosen
Indicates that one entity is the geographic or administrative region in which the referenced city is located.
-
D.
regionOfTown
Indicates that one entity is a specific area or district that forms part of a town.
-
E.
cityOrArea
Indicates that the subject is a city or a broader geographic area associated with the object.
- 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_69f0bd461c208190bec20bbf24e02cc5 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69fd7b0503a08190ba07338365b6fcc9 |
completed | May 8, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69fd7a9733dc81909199f453c0cc2bc1 |
completed | May 8, 2026, 5:54 a.m. |
Created at: April 28, 2026, 4:38 p.m.