Triple
T10863764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muskoka Steamships |
E256473
|
entity |
| Predicate | RMS SegwunStatus |
P96127
|
FINISHED |
| Object | oldest operating steam-driven passenger vessel in North America |
—
|
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: oldest operating steam-driven passenger vessel in North America | Statement: [Muskoka Steamships, RMS SegwunStatus, oldest operating steam-driven passenger vessel in North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RMS SegwunStatus Context triple: [Muskoka Steamships, RMS SegwunStatus, oldest operating steam-driven passenger vessel in North America]
-
A.
sankOnMaidenVoyage
Indicates that the subject vessel sank during its very first voyage.
-
B.
missionAtTimeOfSinking
Indicates that a vessel was engaged in a specific mission or operational role at the time it sank.
-
C.
legalStatusAtTimeOfSinking
Indicates the legal status or condition that applied to an entity at the specific time it sank.
-
D.
placeOfSinking
Indicates the location where an object or entity sank or was submerged.
-
E.
sankOn
Indicates that one entity moved downward and became submerged or lower in level relative to another entity or reference point.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75152f93081909a8186bab5efaf97 |
completed | April 9, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:20 p.m.