Triple
T1003927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Africa |
E21665
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Mount Kilimanjaro |
E12121
|
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: Mount Kilimanjaro | Statement: [East Africa, contains, Mount Kilimanjaro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Kilimanjaro Context triple: [East Africa, contains, Mount Kilimanjaro]
-
A.
Mount Kilimanjaro
chosen
Mount Kilimanjaro is a massive dormant stratovolcano in northeastern Tanzania and the tallest mountain in Africa, famed for its snow-capped summit rising above the surrounding savanna.
-
B.
Mount Kenya
Mount Kenya is an extinct stratovolcano in central Kenya and Africa’s second-highest mountain, renowned for its rugged peaks, glaciers, and alpine ecosystems.
-
C.
Chogolisa
Chogolisa is a prominent, heavily glaciated mountain peak in the Karakoram range of the Himalayas, known for its challenging climbing routes and severe weather conditions.
-
D.
Mount Nyangani
Mount Nyangani is a prominent mountain in eastern Zimbabwe known for its scenic highland landscapes and status as a popular hiking destination.
-
E.
Gigiri
Gigiri is an affluent diplomatic and residential district in Nairobi, Kenya, known for hosting major international institutions and embassies.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4ff614081909478500ada1f5059 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a1ecddc8190b954d16c6e269498 |
completed | March 7, 2026, 1:37 p.m. |
Created at: March 1, 2026, 7:41 p.m.