Triple
T1583842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kigoma |
E34026
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object | Kigoma Port |
E34026
|
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: Kigoma Port | Statement: [Kigoma, hasPort, Kigoma Port]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kigoma Port Context triple: [Kigoma, hasPort, Kigoma Port]
-
A.
Kigoma
chosen
Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
-
B.
Gombe
Gombe is a region in western Tanzania best known for its national park where pioneering primatologist Jane Goodall conducted her landmark chimpanzee research.
-
C.
Gombe
Gombe is a major city in northeastern Nigeria that serves as the capital and economic hub of Gombe State.
-
D.
Port of Nacala
The Port of Nacala is a deep-water seaport in northern Mozambique that serves as a major regional hub for maritime trade and transport in southeastern Africa.
-
E.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
- 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908f0e72c8190bb7a2a0c77379060 |
completed | March 5, 2026, 4:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4698cde88190a113cb7cebc3df1e |
completed | March 8, 2026, 9:51 a.m. |
Created at: March 4, 2026, 7:27 p.m.