Triple
T1128839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cameroon |
E24780
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Garoua |
E129704
|
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: Garoua | Statement: [Cameroon, majorCity, Garoua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garoua Context triple: [Cameroon, majorCity, Garoua]
-
A.
Garoua
chosen
Garoua is a major city in northern Cameroon that serves as an important commercial and administrative center and a key hub for river and overland transport in the region.
-
B.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
C.
Lokoja
Lokoja is a city in central Nigeria located at the strategic confluence of the Niger and Benue rivers and serves as the capital of Kogi State.
-
D.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
E.
Manouria
Manouria is a genus of large, primarily Asian tortoises known for including some of the most primitive living tortoise species.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bbdea9b88190a88da718bf5c1897 |
completed | March 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac7f2dc92481909ee6d9d6d4257f1b |
completed | March 7, 2026, 7:40 p.m. |
Created at: March 1, 2026, 7:44 p.m.