Triple
T21961650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexis Argüello |
E542344
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Managua |
—
|
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: Managua | Statement: [Alexis Argüello, placeOfBirth, Managua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Managua Context triple: [Alexis Argüello, placeOfBirth, Managua]
-
A.
Managua
chosen
Managua is the capital and largest city of Nicaragua, located on the southwestern shore of Lake Managua in Central America.
-
B.
Malabo
Malabo is the largest city and main economic and administrative center of Equatorial Guinea, located on the northern coast of Bioko Island in the Gulf of Guinea.
-
C.
Bangui
Bangui is the capital and largest city of the Central African Republic, serving as its political, economic, and cultural center.
-
D.
Bangui
Bangui is a coastal municipality in Ilocos Norte, Philippines, best known for its iconic wind farm of giant turbines along the shoreline.
-
E.
Juigalpa
Juigalpa is a city in central Nicaragua that serves as the capital of the Chontales Department and a regional hub for agriculture and cattle ranching.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124572738819098cc669aafa53cc6 |
completed | April 28, 2026, 9:19 p.m. |
Created at: April 16, 2026, 8 p.m.