Triple
T12178923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MV Captain Keith Tibbetts wreck |
E290164
|
entity |
| Predicate | wasSunkAs |
P103606
|
FINISHED |
| Object | artificial reef |
—
|
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: artificial reef | Statement: [MV Captain Keith Tibbetts wreck, wasSunkAs, artificial reef]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasSunkAs Context triple: [MV Captain Keith Tibbetts wreck, wasSunkAs, artificial reef]
-
A.
sunkBy
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
-
B.
shipTypeSunk
Indicates that a particular type of ship has been sunk as a result of some event or action.
-
C.
sunkDuring
Indicates that one entity was sunk in the course of, or as a result of, the event or time period represented by another entity.
-
D.
shipsSunkOrTotalLoss
Indicates that the referenced ships were sunk or otherwise rendered a total loss (permanently unusable).
-
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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91a83012c81908d04bbab5fdcd8c2 |
completed | April 10, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69d91510a258819090ef8fbdc2d8707b |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d91a7e0fc081909ec9769231e728a4 |
completed | April 10, 2026, 3:42 p.m. |
Created at: April 8, 2026, 9:50 p.m.