Triple
T10295235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devil’s Pool |
E241467
|
entity |
| Predicate | languageLocal |
P18209
|
FINISHED |
| Object | Bemba |
E286634
|
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: Bemba | Statement: [Devil’s Pool, languageLocal, Bemba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bemba Context triple: [Devil’s Pool, languageLocal, Bemba]
-
A.
Mbanderu
Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
-
B.
AbaBemba
AbaBemba are a major Bantu ethnic group primarily found in northern Zambia, known for their rich cultural traditions, centralized chieftaincy, and historical Bemba Kingdom.
-
C.
Lubemba
Lubemba is the traditional kingdom and cultural heartland of the Bemba people in what is now northern Zambia.
-
D.
Ngbandi
Ngbandi is a Central African language spoken primarily in the Democratic Republic of the Congo and the Central African Republic, known for its role as a regional lingua franca and its inclusion in the Ubangian language family.
-
E.
Bemba language
chosen
Bemba is a major Bantu language spoken primarily in Zambia, serving as one of the country’s most widely used lingua francas in daily life, education, and media.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d5e0f88190be3e23ba2511a1e9 |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d23f49081909aea149c6b219354 |
completed | April 9, 2026, 3:29 a.m. |
Created at: April 6, 2026, 11:43 a.m.