Triple
T6261827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Francisco River mouth |
E140317
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object | Penedo |
E139547
|
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: Penedo | Statement: [São Francisco River mouth, nearCity, Penedo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penedo Context triple: [São Francisco River mouth, nearCity, Penedo]
-
A.
Penedo
chosen
Penedo is a historic riverside city in the Brazilian state of Alagoas, known for its colonial architecture and cultural heritage along the São Francisco River.
-
B.
Serra
Serra is a Spanish surname most famously associated with Junípero Serra, the 18th-century Franciscan friar who founded several missions in what is now California.
-
C.
Morro Branco
Morro Branco is a famous beach in the Brazilian state of Ceará, known for its colorful sand cliffs, labyrinthine sand formations, and scenic coastal landscapes.
-
D.
Pico Ruivo
Pico Ruivo is the tallest mountain on the Portuguese island of Madeira, renowned for its panoramic hiking trails and dramatic volcanic landscapes.
-
E.
Rocha
Rocha is a coastal department in southeastern Uruguay known for its beaches, lagoons, and ecotourism.
- 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_69c008c95c5c819084bd3dd56133d84d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06386a7b48190b032edd12078c5bc |
completed | March 22, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c2444a71b081908b7686034ce7e01b |
completed | March 24, 2026, 7:59 a.m. |
Created at: March 22, 2026, 4:25 p.m.