Triple
T20081952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngorongoro Crater |
E500022
|
entity |
| Predicate | hasAccessTown |
P22318
|
FINISHED |
| Object | Karatu |
—
|
NE NERFINISHED |
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: Karatu | Statement: [Ngorongoro Crater, hasAccessTown, Karatu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karatu Context triple: [Ngorongoro Crater, hasAccessTown, Karatu]
-
A.
Karatu
chosen
Karatu is a small town in northern Tanzania that serves as a popular gateway to the Ngorongoro Conservation Area and Serengeti National Park.
-
B.
Uhuru Peak
Uhuru Peak is the highest summit of Mount Kilimanjaro and the tallest point in Africa, renowned as a major goal for trekkers and climbers worldwide.
-
C.
Mlima Meru
Mlima Meru is the Swahili name for Mount Meru, a prominent active stratovolcano and popular trekking destination in northern Tanzania near Mount Kilimanjaro.
-
D.
Gigiri
Gigiri is an affluent diplomatic and residential district in Nairobi, Kenya, known for hosting major international institutions and embassies.
-
E.
Mount Saramati
Mount Saramati is a prominent peak in Northeast India, known for its rugged terrain, rich biodiversity, and panoramic views over the India–Myanmar border region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e665588a9c8190886b693b13a215a8 |
completed | April 20, 2026, 5:41 p.m. |
Created at: April 11, 2026, 3:41 p.m.