Triple
T4760676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union of Ibero-American Capital Cities |
E105689
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Bissau |
E163653
|
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: Bissau | Statement: [Union of Ibero-American Capital Cities, hasMember, Bissau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bissau Context triple: [Union of Ibero-American Capital Cities, hasMember, Bissau]
-
A.
Bissau
chosen
Bissau is the largest city and principal port of Guinea-Bissau, serving as its political, economic, and cultural center.
-
B.
Conakry
Conakry is the capital and largest city of Guinea, serving as its main economic, cultural, and administrative center on the Atlantic coast of West Africa.
-
C.
Banjul
Banjul is the capital and principal port city of The Gambia, located on an island at the mouth of the Gambia River in West Africa.
-
D.
Bamako
Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
-
E.
Serekunda
Serekunda is the most populous urban center and a major commercial hub in The Gambia.
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650eefe08190b99f9f01b121dbfd |
completed | March 20, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a7c72c48190a562d6261e323b4b |
completed | March 21, 2026, 6:28 a.m. |
Created at: March 20, 2026, 1:20 p.m.