Triple
T20954390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weep Not, Child |
E516061
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Njoroge |
E1459545
|
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: Njoroge | Statement: [Weep Not, Child, hasCharacter, Njoroge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Njoroge Context triple: [Weep Not, Child, hasCharacter, Njoroge]
-
A.
Njoroge
chosen
Njoroge is the young Kenyan protagonist of Ngũgĩ wa Thiong’o’s novel "Weep Not, Child," whose coming-of-age unfolds amid the turmoil of colonial rule and the Mau Mau uprising.
-
B.
Kamau
Kamau is a masculine given name of African origin, notably borne by American comedian and television host W. Kamau Bell.
-
C.
Rutenga
Rutenga is a small town in southern Zimbabwe that serves as an important local commercial and transport hub within Mwenezi District.
-
D.
Njoro
Njoro is a town in Kenya’s Rift Valley region known for its agricultural activities and as the home of Egerton University.
-
E.
Oshindali
Oshindali is a regional dialect of the Oshiwambo language spoken primarily by communities in northern Namibia and southern Angola.
- 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fae154a481909f235165a46d0910 |
completed | April 21, 2026, 4:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a092faf16b0819097a3eeee0155a3dd |
completed | May 17, 2026, 3:02 a.m. |
Created at: April 16, 2026, 1:28 p.m.