Triple
T11062658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pilar, Cebu |
E261545
|
entity |
| Predicate | developmentLevelComparedToMainlandCebu |
P97588
|
FINISHED |
| Object | less developed |
—
|
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: less developed | Statement: [Pilar, Cebu, developmentLevelComparedToMainlandCebu, less developed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: developmentLevelComparedToMainlandCebu Context triple: [Pilar, Cebu, developmentLevelComparedToMainlandCebu, less developed]
-
A.
approxDistanceFromCebuCity
Indicates that one entity is located at an approximate distance from Cebu City.
-
B.
developmentLevel
Indicates the degree or stage of progress, advancement, or maturity that something has reached in its growth or evolution.
-
C.
rankByAreaInPhilippines
Indicates the relative ordering of entities based on their area size specifically within the Philippines.
-
D.
approxTravelTimeFromCebuCity
Indicates the estimated amount of time it typically takes to travel from Cebu City to another location.
-
E.
urbanizationLevel
Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
- F. None of above. chosen
Provenance (4 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798eb838c819089a89c55209c0295 |
completed | April 9, 2026, 12:17 p.m. |
| PD | Predicate disambiguation | batch_69d74411d9e881908c0eeafa0f38e4b6 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750c99f9881908ee2b01b6ce4b3a1 |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:26 p.m.