Triple
T22539962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oregun |
E557260
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Maryland, Lagos |
—
|
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: Maryland, Lagos | Statement: [Oregun, locatedNear, Maryland, Lagos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maryland, Lagos Context triple: [Oregun, locatedNear, Maryland, Lagos]
-
A.
Maryland, Lagos
chosen
Maryland, Lagos is a busy residential and commercial district on Lagos Mainland known for its strategic location and major transport links.
-
B.
Entre Lagos
Entre Lagos is a small lakeside town in southern Chile known as a gateway to the Puyehue and Rupanco lake region and nearby Andean landscapes.
-
C.
Lagos–New York
Lagos–New York is a long-haul intercontinental air route linking Nigeria’s largest city with the United States’ largest city.
-
D.
General Lagos
General Lagos is a small town in the Rosario Department of Santa Fe Province, Argentina, known for its rural character and proximity to the city of Rosario.
-
E.
General Lagos
General Lagos is a remote high-altitude Chilean commune in the Arica y Parinacota Region, bordering Peru and Bolivia in the Andean plateau.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f3196fc819098deffb0c7932ccc |
completed | April 29, 2026, 1:30 a.m. |
Created at: April 16, 2026, 8:51 p.m.