Triple
T2392298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morona-Santiago Province |
E48969
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Macas |
E263067
|
NE 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: Macas | Statement: [Morona-Santiago Province, hasSettlement, Macas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macas Context triple: [Morona-Santiago Province, hasSettlement, Macas]
-
A.
Macas
chosen
Macas is a city in southeastern Ecuador that serves as an administrative and commercial hub in the Amazonian region.
-
B.
Mamanguape
Mamanguape is a municipality in the Brazilian state of Paraíba, known for its historical colonial architecture and location near the Mamanguape River on the state’s northern coast.
-
C.
Bacong
Bacong is a coastal municipality in the province of Negros Oriental in the Philippines, known for its historic church and proximity to Dumaguete City.
-
D.
Calabarzon
Calabarzon is a populous and industrialized region in the southern part of Luzon in the Philippines, known for its mix of urban centers, agricultural areas, and manufacturing hubs.
-
E.
Malabuyoc
Malabuyoc is a coastal municipality in the southwestern part of Cebu province in the Philippines, known for its hot springs and scenic seaside landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88aa5f63081908d07fd302029fcbd |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc87587708190a7f2bc473a898bc2 |
completed | March 7, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef09854fc8190bab0415e3815a920 |
completed | March 9, 2026, 4:08 p.m. |
Created at: March 4, 2026, 7:57 p.m.