Triple
T16188842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debub Region |
E392879
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Segeneiti |
E392883
|
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: Segeneiti | Statement: [Debub Region, contains, Segeneiti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Segeneiti Context triple: [Debub Region, contains, Segeneiti]
-
A.
Segeneiti
chosen
Segeneiti is a town in southern Eritrea known for its agricultural surroundings and role as a local commercial center.
-
B.
Genetz
Genetz is a Finnish surname most notably associated with Arvid Genetz, a 19th-century linguist, poet, and politician.
-
C.
Geno
Geno is a young male deer character from Disney's Bambi franchise, depicted as the son of Bambi and Faline.
-
D.
Geno
Geno is the widely used nickname of Hall of Fame University of Connecticut women's basketball coach Geno Auriemma.
-
E.
Geneina
Geneina is a city in western Sudan that serves as a major urban center in Darfur and a focal point for the Masalit people.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d3a8e48190bdf29a633f4b0490 |
completed | April 17, 2026, 12:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff0750f08190a2fce65124d8dcc0 |
completed | May 10, 2026, 3:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.