Triple
T4733649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anseba |
E105070
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Maekel Region |
E401228
|
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: Maekel Region | Statement: [Anseba, borders, Maekel Region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maekel Region Context triple: [Anseba, borders, Maekel Region]
-
A.
Maekel Region
chosen
Maekel Region is a central administrative region of Eritrea that includes the nation’s capital, Asmara, and serves as its political and economic hub.
-
B.
Isaac Region
Isaac Region is a local government area in central Queensland, Australia, known for its extensive coal mining operations and rural communities.
-
C.
Omusati Region
Omusati Region is an administrative region in northwestern Namibia known for its predominantly rural communities, subsistence agriculture, and proximity to the Angolan border.
-
D.
Karas Region
Karas Region is the southernmost administrative region of Namibia, known for its arid landscapes, desert scenery, and coastal towns along the Atlantic Ocean.
-
E.
Racha region
Racha region is a mountainous area in northwestern Georgia known for its scenic landscapes, traditional villages, and wine production.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6467a1fc819089485b4d76e0edc4 |
completed | March 20, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be10acf7488190946b31f95114d459 |
completed | March 21, 2026, 3:29 a.m. |
Created at: March 20, 2026, 1:19 p.m.