Triple
T7878777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teshie |
E182924
|
entity |
| Predicate | hasNeighbouringTown |
P3883
|
FINISHED |
| Object | Nungua |
E182925
|
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: Nungua | Statement: [Teshie, hasNeighbouringTown, Nungua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nungua Context triple: [Teshie, hasNeighbouringTown, Nungua]
-
A.
Nungua
chosen
Nungua is a coastal town and suburb of Accra in southern Ghana, known for its fishing community and vibrant local culture.
-
B.
Lugazi
Lugazi is a town in central Uganda known for its sugar plantations and location along the Kampala–Jinja highway.
-
C.
Kalambo
Kalambo is an agricultural research station site in the Lake Tanganyika region of Tanzania, known for supporting tropical crop and farming systems research.
-
D.
Wainganga
Wainganga is a major river in central India that flows through the states of Madhya Pradesh and Maharashtra before joining other rivers on its way to the Godavari basin.
-
E.
Ruganzu River
Ruganzu River is a waterway in Rwanda that flows through the capital city, Kigali.
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39bd64e481909f699e7dd2818b8f |
completed | March 31, 2026, 3:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc93556f0c8190b072c3ec4c8e93bd |
completed | April 1, 2026, 3:39 a.m. |
Created at: March 30, 2026, 4:57 p.m.