Triple
T12851550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Congo region |
E307333
|
entity |
| Predicate | majorTown |
P316
|
FINISHED |
| Object | Matadi |
E161892
|
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: Matadi | Statement: [Lower Congo region, majorTown, Matadi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matadi Context triple: [Lower Congo region, majorTown, Matadi]
-
A.
Matadi
chosen
Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
-
B.
Nsanje
Nsanje is a town in southern Malawi near the border with Mozambique, known as a key transport and trading center in the Lower Shire Valley.
-
C.
Lubumbashi
Lubumbashi is the second-largest city in the Democratic Republic of the Congo and a major mining and commercial center in the southeastern part of the country.
-
D.
Chegutu
Chegutu is a town in central northern Zimbabwe known for its agricultural activities and gold mining.
-
E.
Kapiri Mposhi
Kapiri Mposhi is a town in central Zambia that serves as a key rail and road junction linking the country to Tanzania and other regions.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97020eacc81909357b3398d17dc49 |
completed | April 10, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a549fc188190a7dfcf16faa5e415 |
completed | May 3, 2026, 1:30 a.m. |
Created at: April 9, 2026, 5:36 p.m.