Triple
T25275952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunduma–Nakonde border |
E633695
|
entity |
| Predicate | connectsPortToHinterland |
P168885
|
FINISHED |
| Object | Port of Dar es Salaam |
—
|
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: Port of Dar es Salaam | Statement: [Tunduma–Nakonde border, connectsPortToHinterland, Port of Dar es Salaam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsPortToHinterland Context triple: [Tunduma–Nakonde border, connectsPortToHinterland, Port of Dar es Salaam]
-
A.
connectsPortRegion
Indicates that one entity serves as a linkage or interface between a specific port and a defined region.
-
B.
connectsCentralAreaTo
Indicates a relationship where one element serves as a link or pathway between a central area and another location or component.
-
C.
portConnections
Indicates that there exists a connection or linkage between two ports or interfaces.
-
D.
connectsIslandWithMainland
Indicates a relationship where a structure or route provides a direct link between an island and the mainland.
-
E.
linkedToPort
Indicates that one entity is connected or associated with a specific port, such as a network, hardware, or interface port.
- F. None of above. chosen
Provenance (4 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_69e75a92f48881909974ff9c11150a2e |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f67866e9248190b7ba218f9ca2ae8d |
completed | May 2, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f675fd59608190b246383435e68fce |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676c35f3481909b9ba18a5662d6ce |
completed | May 2, 2026, 10:12 p.m. |
Created at: April 21, 2026, 1:17 p.m.