Triple
T7844977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betania Dam |
E181900
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Campoalegre |
E177721
|
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: Campoalegre | Statement: [Betania Dam, nearbyCity, Campoalegre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Campoalegre Context triple: [Betania Dam, nearbyCity, Campoalegre]
-
A.
Campoalegre
chosen
Campoalegre is a municipality and town in southwestern Colombia, located in the Huila Department and known for its agricultural production.
-
B.
Itanhaém
Itanhaém is a coastal municipality in southeastern Brazil known for its beaches, historic colonial center, and tourism along the São Paulo state shoreline.
-
C.
Magé
Magé is a municipality in the state of Rio de Janeiro, Brazil, located in the metropolitan region of Rio de Janeiro and known for its coastal setting and historical significance.
-
D.
Santo Amaro
Santo Amaro is a central neighborhood in Recife, Brazil, known for its mix of residential areas, commerce, and important urban infrastructure.
-
E.
Jundiaí
Jundiaí is a mid-sized industrial and logistics city in southeastern Brazil known for its strong economy and high quality of life.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb163d92fc8190a4efcb08d6b3d404 |
completed | March 31, 2026, 12:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5ae9758c819091e270343ed289aa |
completed | March 31, 2026, 5:26 a.m. |
Created at: March 30, 2026, 4:48 p.m.