Triple
T6580022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kisangani |
E157267
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Boyoma Falls |
E610107
|
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: Boyoma Falls | Statement: [Kisangani, namedAfter, Boyoma Falls]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boyoma Falls Context triple: [Kisangani, namedAfter, Boyoma Falls]
-
A.
Tanda Falls
Tanda Falls is a scenic waterfall and popular natural getaway located near Mirzapur in Uttar Pradesh, India.
-
B.
Diyaluma Falls
Diyaluma Falls is one of Sri Lanka’s tallest and most scenic waterfalls, renowned for its dramatic cascades and natural rock pools that attract many visitors.
-
C.
Gurara Falls
Gurara Falls is a major scenic waterfall and popular tourist attraction in central Nigeria, renowned for its impressive cascades and natural beauty.
-
D.
Lugard Falls
Lugard Falls is a series of spectacular white-water rapids and eroded rock formations on the Galana River in Kenya, known for its dramatic scenery and wildlife viewing.
-
E.
Zongo Falls
chosen
Zongo Falls is a scenic waterfall and popular natural attraction located in the Kongo Central Province of the Democratic Republic of the Congo.
- 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_69c6882b3a108190b3a9eb343ae4162c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae8ef4d08190b4c88aa0c15fe91c |
completed | March 27, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f78896b48190a8d993c207d01a7e |
completed | March 27, 2026, 9:32 p.m. |
Created at: March 27, 2026, 1:54 p.m.