Triple
T19560155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gash River |
E489426
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object | Kassala |
—
|
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: Kassala | Statement: [Gash River, flowsNear, Kassala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kassala Context triple: [Gash River, flowsNear, Kassala]
-
A.
Kassala
chosen
Kassala is a city in eastern Sudan near the Eritrean border, known as a regional trade center and for its striking granite hills and cultural diversity.
-
B.
Zintan
Zintan is a town in western Libya known for its role in the Libyan Civil War and for being controlled by powerful local militias.
-
C.
Safaga
Safaga is a coastal town and port on Egypt’s Red Sea coast known for its diving sites, black sand beaches, and therapeutic tourism.
-
D.
Tantu
Tantu is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its exploration of complex social and philosophical themes.
-
E.
Ain Defla
Ain Defla is a town and provincial capital in northern Algeria known for its agricultural surroundings and strategic location along major transport routes.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f731ae48190ade295c15db7f8ed |
completed | April 20, 2026, 3 p.m. |
Created at: April 10, 2026, 1:42 p.m.