Triple
T31923253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cumberland Island ferry |
E815030
|
entity |
| Predicate | regulatesCapacity |
P192229
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Cumberland Island ferry, regulatesCapacity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatesCapacity Context triple: [Cumberland Island ferry, regulatesCapacity, true]
-
A.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
B.
laterCapacity
Indicates that one entity’s capacity or capability occurs, becomes available, or is realized at a later time than another’s.
-
C.
totalCapacity
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
D.
stageCapacity
Indicates the maximum number of people or amount of occupancy that a particular stage can accommodate.
-
E.
classCapacitySecond
Indicates that the second class in a sequence has a specified maximum number of participants or seats.
- F. None of above. chosen
Provenance (4 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_69f348f1df848190851bbfb988da3414 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69fd026757a081909911a59a78652709 |
completed | May 7, 2026, 9:21 p.m. |
Created at: May 1, 2026, 12:03 a.m.