Triple
T1604707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ga people |
E34474
|
entity |
| Predicate | subgroup |
P10
|
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: [Ga people, subgroup, Nungua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nungua Context triple: [Ga people, subgroup, 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.
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.
-
C.
Mvita
Mvita is an alternative name for Kimvita, a historic Swahili settlement and cultural center on the coast of present-day Kenya.
-
D.
Tamba
Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
-
E.
Kasulu
Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of 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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9096a165c8190aec1d2ae6bd10e18 |
completed | March 5, 2026, 4:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58c42c6c8190b245c3434e6bbcf8 |
completed | March 8, 2026, 11:08 a.m. |
Created at: March 4, 2026, 7:28 p.m.