Triple
T26275221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewes-Rehoboth Hundred |
E660546
|
entity |
| Predicate | containsFerryService |
P1737
|
FINISHED |
| Object | Cape May–Lewes Ferry |
—
|
NE NERFINISHED |
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: Cape May–Lewes Ferry | Statement: [Lewes-Rehoboth Hundred, containsFerryService, Cape May–Lewes Ferry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsFerryService Context triple: [Lewes-Rehoboth Hundred, containsFerryService, Cape May–Lewes Ferry]
-
A.
hasFerryService
chosen
Indicates that there is an operational ferry connection or transport service available between the related locations or entities.
-
B.
hasFerryComponent
Indicates that something includes or is associated with a ferry-related part, feature, or segment within its structure or operation.
-
C.
hasFerryType
Indicates that an entity (such as a ferry route or service) is associated with a specific type or category of ferry.
-
D.
requiresFerries
Indicates that traveling between two locations involves or depends on the use of one or more ferries.
-
E.
hasFerryPort
Indicates that a place serves as a location where ferries regularly dock to load and unload passengers or cargo.
- 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_69ee812960d081909cff6085cc9fa3a6 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
Created at: April 26, 2026, 9:55 p.m.