Triple
T28735927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saclepea |
E730798
|
entity |
| Predicate | hasRoadConnections |
P11435
|
FINISHED |
| Object | other towns in Nimba County |
—
|
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: other towns in Nimba County | Statement: [Saclepea, hasRoadConnections, other towns in Nimba County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadConnections Context triple: [Saclepea, hasRoadConnections, other towns in Nimba County]
-
A.
hasRoadConnectionRegion
Indicates that there is a road-based transportation link connecting one region to another.
-
B.
hasRoads
Indicates that there exist constructed road connections linking the related entities.
-
C.
hasConnectingRoadNumber
Indicates that there exists a road connection between two locations or road segments identified by a specific road number.
-
D.
connectsRoadNetwork
Indicates that one entity is linked to another as part of the same road network, enabling continuous vehicular or transport connectivity between them.
-
E.
linkedByRoadTo
chosen
Indicates that two locations are directly connected to each other by a road suitable for travel.
- F. None of above.
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_69f043eae0908190b28ce314686247d7 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: April 28, 2026, 6 a.m.