Triple
T10541481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Region of Brazil |
E248704
|
entity |
| Predicate | containsAdministrativeDivision |
P747
|
FINISHED |
| Object | Acre |
E480613
|
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: Acre | Statement: [North Region of Brazil, containsAdministrativeDivision, Acre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Acre Context triple: [North Region of Brazil, containsAdministrativeDivision, Acre]
-
A.
Acre
Acre is an ancient port city on the Mediterranean coast of present-day Israel, renowned for its well-preserved Crusader and Ottoman architecture and its long, strategic history.
-
B.
Acre (state)
chosen
Acre is a remote, heavily forested state in Brazil’s western Amazon region, known for its vast rainforest, rubber-tapping history, and rich Indigenous cultures.
-
C.
Felda
Felda is a small river in central Germany that flows through Hesse and Thuringia before joining the Werra.
-
D.
Areal
Areal is a small municipality in the mountainous Região Serrana of Rio de Janeiro state in southeastern Brazil.
-
E.
Luas
Luas is Dublin’s modern light rail tram system, providing frequent urban and suburban public transport across the city and its surrounding areas.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a5918648190b16c2d1bc1bf015f |
completed | April 7, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9341d96c08190a6ba644b9acfe2c8 |
completed | April 10, 2026, 5:32 p.m. |
Created at: April 6, 2026, 12:32 p.m.