Triple
T34966760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ikoyi |
E1008420
|
entity |
| Predicate | hasRoadConnectivityPattern |
P74765
|
FINISHED |
| Object | network of access roads and bridges |
—
|
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: network of access roads and bridges | Statement: [Ikoyi, hasRoadConnectivityPattern, network of access roads and bridges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadConnectivityPattern Context triple: [Ikoyi, hasRoadConnectivityPattern, network of access roads and bridges]
-
A.
hasRoadConfiguration
Indicates that there exists a specific arrangement or layout of roads associated with or characterizing an entity.
-
B.
hasRoadConnectionRegion
Indicates that there is a road-based transportation link connecting one region to another.
-
C.
hasConnectingRoadNumber
Indicates that there exists a road connection between two locations or road segments identified by a specific road number.
-
D.
hasRoadNetworkType
chosen
Indicates the type or classification of road network associated with or present in an entity.
-
E.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
- 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe766490c081908c49c8cc07d0ae9b |
completed | May 8, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69fe75bb5f4481908572a5ffcbdc5154 |
completed | May 8, 2026, 11:46 p.m. |
Created at: May 3, 2026, 4 p.m.