Triple
T22055519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribatejo |
E544999
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Cartaxo |
—
|
NE NERFINISHED |
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: Cartaxo | Statement: [Ribatejo, majorCity, Cartaxo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cartaxo Context triple: [Ribatejo, majorCity, Cartaxo]
-
A.
Cartaxo
chosen
Cartaxo is a Portuguese town in the Ribatejo region known historically for its wine production and agricultural surroundings.
-
B.
Gravataí
Gravataí is a municipality in the state of Rio Grande do Sul in southern Brazil, known for its industrial activity and proximity to the Porto Alegre metropolitan area.
-
C.
Oriximiná
Oriximiná is a large municipality in the Brazilian state of Pará, known for its Amazon rainforest areas, river systems, and significant mining and conservation sites.
-
D.
Botucatu
Botucatu is a municipality in southeastern Brazil known for its higher-education institutions, especially São Paulo State University (UNESP), and its surrounding sandstone cliffs and natural landscapes.
-
E.
Garça
Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3377c48190890c17407b9527d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285790948190b21abfb09abbb5e5 |
completed | April 28, 2026, 9:36 p.m. |
Created at: April 16, 2026, 8:26 p.m.