Triple
T291677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberia |
E6007
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Monrovia |
E37770
|
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: Monrovia | Statement: [Liberia, largestCity, Monrovia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monrovia Context triple: [Liberia, largestCity, Monrovia]
-
A.
Monrovia
chosen
Monrovia is the largest city and main economic and administrative center of Liberia, located on the Atlantic coast in West Africa.
-
B.
Port-au-Prince
Port-au-Prince is the capital and largest city of Haiti, serving as the country’s political, economic, and cultural center.
-
C.
Brazzaville
Brazzaville is the capital and largest city of the Republic of the Congo, located on the Congo River directly across from Kinshasa in Central Africa.
-
D.
Dakar
Dakar is the capital and largest city of Senegal, located on the Atlantic coast and serving as a major political, economic, and cultural hub of West Africa.
-
E.
Paramaribo
Paramaribo is the capital and largest city of Suriname, known for its diverse population and historic colonial architecture along the Suriname River.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e975d2c0819082bbf6a0f3d928af |
completed | Feb. 28, 2026, 1:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3a5d315ec819090df0fcee8d3d493 |
completed | March 1, 2026, 2:34 a.m. |
Created at: Feb. 28, 2026, 1:06 p.m.