Triple
T6988565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constitutive Act of the African Union |
E162027
|
entity |
| Predicate | adoptionPlace |
P1677
|
FINISHED |
| Object | Lomé, Togo |
E71688
|
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: Lomé, Togo | Statement: [Constitutive Act of the African Union, adoptionPlace, Lomé, Togo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lomé, Togo Context triple: [Constitutive Act of the African Union, adoptionPlace, Lomé, Togo]
-
A.
Lomé
chosen
Lomé is the coastal capital and largest city of Togo, serving as a key economic and cultural hub in West Africa.
-
B.
Serekunda
Serekunda is the most populous urban center and a major commercial hub in The Gambia.
-
C.
Libreville
Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
-
D.
Port-Gentil
Port-Gentil is Gabon's second-largest city and a major oil and port hub located on the country's Atlantic coast.
-
E.
Bertoua
Bertoua is a major city in eastern Cameroon that serves as an important administrative and commercial hub for the surrounding forested region.
- 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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbbd926c8190a8b60527bd553fa3 |
completed | March 27, 2026, 7:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c761d3f07081908892cdcac8e0917c |
completed | March 28, 2026, 5:06 a.m. |
Created at: March 27, 2026, 2:32 p.m.