Triple
T32357077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marblehead, Ohio |
E826762
|
entity |
| Predicate | hasNearbyFerryService |
P1737
|
FINISHED |
| Object | ferries to Lake Erie islands |
—
|
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: ferries to Lake Erie islands | Statement: [Marblehead, Ohio, hasNearbyFerryService, ferries to Lake Erie islands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyFerryService Context triple: [Marblehead, Ohio, hasNearbyFerryService, ferries to Lake Erie islands]
-
A.
hasNearbyFerryRoute
Indicates that there is a ferry route located close to the referenced entity.
-
B.
hasNearbyFerryPort
Indicates that one location is situated close enough to another location that serves as a ferry port to be considered nearby.
-
C.
hasFerryService
chosen
Indicates that there is an operational ferry connection or transport service available between the related locations or entities.
-
D.
hasFerryComponent
Indicates that something includes or is associated with a ferry-related part, feature, or segment within its structure or operation.
-
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_69f34915a2588190bb3178f5ec2f48f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff45793d5c81909dc503ad1f714ee2 |
completed | May 9, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69ff41cb0e088190a6e9b03cb20e5fad |
completed | May 9, 2026, 2:16 p.m. |
Created at: May 1, 2026, 12:49 a.m.