Triple
T16188433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anseba Region |
E392869
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Anseba River |
E526023
|
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: Anseba River | Statement: [Anseba Region, namedAfter, Anseba River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anseba River Context triple: [Anseba Region, namedAfter, Anseba River]
-
A.
Anseba River
chosen
The Anseba River is a major seasonal watercourse in Eritrea that flows from the central highlands toward the Red Sea basin, supporting agriculture and settlements along its valley.
-
B.
Abasha River
The Abasha River is a waterway in western Georgia that flows through the Samegrelo-Zemo Svaneti region before joining the Rioni River.
-
C.
Sumène River
The Sumène River is a watercourse in south-central France that originates in the Cantal Mountains and flows through the Auvergne region before joining larger river systems.
-
D.
Safi River
The Safi River is a watercourse in northwestern Iran that flows through the city of Maragheh in East Azerbaijan Province.
-
E.
Safi River
The Safi River is a significant tributary watercourse that feeds into eastern India’s Damodar River system.
- 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_6a0139e380bc81908452f6e8666f23ad |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:02 a.m.