Triple
T22618022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Savannah Region |
E558198
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Salaga |
—
|
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: Salaga | Statement: [Savannah Region, hasSettlement, Salaga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salaga Context triple: [Savannah Region, hasSettlement, Salaga]
-
A.
Salaga
chosen
Salaga is a historic town in northern Ghana that once served as a major hub in the trans-Saharan slave trade.
-
B.
Baraya
Baraya is a Spanish-language surname most notably associated with Colombian independence leader Antonio Baraya.
-
C.
Martos
Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
-
D.
Candaba
Candaba is a municipality in the Philippine province of Pampanga known for its vast wetlands and rich bird-watching sites.
-
E.
Alamata
Alamata is a town in northern Ethiopia that serves as a local commercial and administrative center in the southern part of the Tigray Region.
- 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_69e24545a8e08190bfa7482a2c725ff1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f167ef7a148190870334af9c8b79a4 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 2:59 p.m.