Triple
T5322822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobermory, Ontario |
E121713
|
entity |
| Predicate | nearbyShipwreckSite |
P49889
|
FINISHED |
| Object | Fathom Five shipwrecks |
—
|
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: Fathom Five shipwrecks | Statement: [Tobermory, Ontario, nearbyShipwreckSite, Fathom Five shipwrecks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyShipwreckSite Context triple: [Tobermory, Ontario, nearbyShipwreckSite, Fathom Five shipwrecks]
-
A.
hasShipwrecks
chosen
Indicates that one entity contains, includes, or is associated with shipwrecks located within it or under its control.
-
B.
shipwreckEvent
Indicates an event in which a ship is destroyed, stranded, or severely damaged, typically resulting in loss or abandonment at sea or near a shoreline.
-
C.
wreckDiscovery
Indicates that an entity discovers, finds, or identifies a wreck (such as a ruined or destroyed object, vehicle, or structure).
-
D.
placeOfSinking
Indicates the location where an object or entity sank or was submerged.
-
E.
shipwreckUse
Indicates that an entity makes use of, interacts with, or derives benefit from a shipwreck.
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd86f20f008190be7b5848af05f2b8 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd84561c7081909e5937c7816e492c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 1:59 p.m.