Triple
T10509289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mano people |
E247868
|
entity |
| Predicate | borderDistribution |
P94290
|
FINISHED |
| Object | present on both sides of the Liberia–Guinea border |
—
|
LITERAL 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: present on both sides of the Liberia–Guinea border | Statement: [Mano people, borderDistribution, present on both sides of the Liberia–Guinea border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderDistribution Context triple: [Mano people, borderDistribution, present on both sides of the Liberia–Guinea border]
-
A.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
-
B.
boundaryBetween
Indicates that something serves as a dividing line or limit separating two distinct regions, areas, or entities.
-
C.
borderCharacteristic
Indicates that one entity specifies a property, feature, or quality of the border or boundary of another entity.
-
D.
borderPoint
Indicates a point that lies on the boundary between two regions or entities.
-
E.
borderCountrySide
Indicates that one country shares a land border with the side or region of another country.
- F. None of above. chosen
Provenance (4 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509b359ac8190b3683cc6b9c70a71 |
completed | April 7, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d4fe058fcc81909428137d9ffd6d90 |
completed | April 7, 2026, 12:52 p.m. |
Created at: April 6, 2026, 12:26 p.m.