Triple
T20131464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Tanzania |
E490904
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Moshi |
—
|
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: Moshi | Statement: [Northern Tanzania, contains, Moshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moshi Context triple: [Northern Tanzania, contains, Moshi]
-
A.
Moshi
chosen
Moshi is a Tanzanian town in the Kilimanjaro Region that serves as a major gateway and base for climbers ascending Mount Kilimanjaro.
-
B.
Juja
Juja is a rapidly growing urban town in Kenya known for its proximity to Nairobi and its major universities and industries.
-
C.
Limuru
Limuru is a highland town in central Kenya known for its cool climate, tea plantations, and proximity to Nairobi.
-
D.
Zanzibar City
Zanzibar City is the historic and administrative capital of Zanzibar, Tanzania, renowned for its UNESCO-listed Stone Town and rich Swahili, Arab, and colonial heritage.
-
E.
Oshakati
Oshakati is a major northern Namibian town that serves as an important commercial and administrative hub.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66762f0448190b7dbbc665e179ffc |
completed | April 20, 2026, 5:50 p.m. |
Created at: April 11, 2026, 11:31 p.m.