Triple
T9793755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyanza region |
E237667
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Kisii |
E811274
|
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: Kisii | Statement: [Nyanza region, hasTown, Kisii]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kisii Context triple: [Nyanza region, hasTown, Kisii]
-
A.
Kisii
chosen
Kisii is a bustling commercial and administrative town in southwestern Kenya, serving as a key hub for the surrounding agricultural highlands and the Kisii community.
-
B.
Kisoro
Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
-
C.
Apswa
Apswa is the endonym used by the Abkhaz people to refer to themselves and their language.
-
D.
Nungua
Nungua is a coastal town and suburb of Accra in southern Ghana, known for its fishing community and vibrant local culture.
-
E.
Ounianga Kebir
Ounianga Kebir is a remote oasis town in northern Chad, known as part of the Ounianga lake region recognized for its striking desert lakes and unique Saharan landscapes.
- 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_69ca84dc04488190b9c91193976c0960 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda347b6bc8190a99b7dec1650cd46 |
completed | April 1, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc5118a481908a65d730f86c7723 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:28 p.m.