Triple
T20426740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tindyebwa Agaba Wise |
E501021
|
entity |
| Predicate | hasMiddleName |
P143
|
FINISHED |
| Object | Agaba |
—
|
NE NERFINISHED |
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: Agaba | Statement: [Tindyebwa Agaba Wise, hasMiddleName, Agaba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agaba Context triple: [Tindyebwa Agaba Wise, hasMiddleName, Agaba]
-
A.
Agaba
chosen
Agaba is a given name associated with Tindyebwa Agaba Wise, a Rwandan-born human rights activist and adopted son of British actress Emma Thompson.
-
B.
Agbara
Agbara is a prominent industrial and residential town in southwestern Nigeria, known for its large industrial estate and proximity to Lagos.
-
C.
Akpabuyo
Akpabuyo is a coastal local government area in southeastern Nigeria known for its location near Calabar in Cross River State.
-
D.
Ogba
Ogba is an ethnic group and local government area in Rivers State, Nigeria, known for its distinct language and rich cultural traditions.
-
E.
Ogba
Ogba is a bustling mixed-use neighborhood in Lagos, Nigeria, known for its residential estates, markets, and small-to-medium-scale businesses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4aa68fc8190b1a14c55575ef04a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67ba9700481909fa23493f98095d1 |
completed | April 20, 2026, 7:16 p.m. |
Created at: April 16, 2026, 11:30 a.m.