Triple
T14082921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caprivi Strip |
E338911
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Namibia |
E14828
|
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: Namibia | Statement: [Caprivi Strip, partOf, Namibia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namibia Context triple: [Caprivi Strip, partOf, Namibia]
-
A.
Namibia
chosen
Namibia is a sparsely populated country in southwestern Africa known for its dramatic desert landscapes, diverse wildlife, and a legal system influenced by Roman-Dutch law.
-
B.
Botswana
Botswana is a landlocked country in Southern Africa known for its stable democracy, significant diamond resources, and vast wildlife-rich landscapes including the Okavango Delta.
-
C.
Namibia and Botswana
Namibia and Botswana are neighboring countries in Southern Africa known for their vast deserts, rich wildlife, and major river systems that shape their shared ecosystems and borders.
-
D.
Tiszanána
Tiszanána is a village in northern Hungary known for its proximity to the Tisza River and recreational areas around Lake Tisza.
-
E.
Eswatini
Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ede40048190b465e909565730c1 |
completed | April 14, 2026, 3:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0a3e55c81909b52f618e9076dd2 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:21 p.m.