Triple
T18003525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coral Harbour |
E430685
|
entity |
| Predicate | roadConnectionToOtherCommunities |
P11435
|
FINISHED |
| Object | none |
—
|
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: none | Statement: [Coral Harbour, roadConnectionToOtherCommunities, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadConnectionToOtherCommunities Context triple: [Coral Harbour, roadConnectionToOtherCommunities, none]
-
A.
connectsInlandCommunitiesTo
Indicates a relationship in which something serves as a link or conduit between inland communities and another place, system, or network.
-
B.
roadConnectivityStatus
Indicates the current state of whether and how well two locations are connected by a road network.
-
C.
connectsMunicipalities
Indicates a relationship where one entity serves as a link or route that joins two or more municipalities.
-
D.
linkedByRoadTo
chosen
Indicates that two locations are directly connected to each other by a road suitable for travel.
-
E.
connectsCityTo
Indicates a relationship in which a route, infrastructure, or link joins one city to another, enabling connection or interaction between them.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b3ea60608190b977644e946407b7 |
completed | April 19, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.