Triple
T36288000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imus, Cavite |
E893142
|
entity |
| Predicate | hasPopulationRankInCavite |
P1026
|
FINISHED |
| Object | one of the most populous cities in Cavite |
—
|
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: one of the most populous cities in Cavite | Statement: [Imus, Cavite, hasPopulationRankInCavite, one of the most populous cities in Cavite]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationRankInCavite Context triple: [Imus, Cavite, hasPopulationRankInCavite, one of the most populous cities in Cavite]
-
A.
rankByAreaInPhilippines
Indicates the relative ordering of entities based on their area size specifically within the Philippines.
-
B.
hasNumberOfBarangays
Indicates the total count of barangays associated with a given administrative unit or locality.
-
C.
isHighlyUrbanizedCityBarangay
Indicates that a barangay is located within a city and exhibits a high degree of urban development and urban characteristics.
-
D.
hasPopulationRank
chosen
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
E.
hasUrbanBarangays
Indicates that a place or administrative unit possesses one or more barangays classified as urban.
- 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_69f76e4955c08190b8cfddca34fc0242 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff7eb7189c81909a8f73fbc4c48e02 |
completed | May 9, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69ff7e54e11081908fb5ce10c5aa7b53 |
completed | May 9, 2026, 6:35 p.m. |
Created at: May 3, 2026, 4:09 p.m.