Triple
T2534061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apapa Port |
E56227
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Apapa |
E56227
|
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: Apapa | Statement: [Apapa Port, locatedIn, Apapa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apapa Context triple: [Apapa Port, locatedIn, Apapa]
-
A.
Apapa Port
chosen
Apapa Port is Nigeria’s largest and busiest seaport complex, serving as a major gateway for the country’s international maritime trade in Lagos.
-
B.
Zaria
Zaria is a historic city in northern Nigeria known as an important center of Hausa culture, Islamic scholarship, and trade.
-
C.
Kano
Kano is a major commercial and industrial city in northern Nigeria and one of the country’s oldest urban centers.
-
D.
Afula
Afula is a city in northern Israel often referred to as the "Capital of the Jezreel Valley," serving as a regional commercial and transportation hub.
-
E.
Paipa
Paipa is a Colombian town in the Boyacá Department known for its thermal springs, tourism, and historical significance in the independence era.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd27afe7c8190984e10d3f3d5586b |
completed | March 7, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2bbc416c81908774782420b54664 |
completed | March 9, 2026, 8:21 p.m. |
Created at: March 6, 2026, 9:47 p.m.