Triple
T4045126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter L. Frost shipwreck |
E84046
|
entity |
| Predicate | hasOriginalVesselUse |
P25840
|
FINISHED |
| Object | cargo transport |
—
|
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: cargo transport | Statement: [Walter L. Frost shipwreck, hasOriginalVesselUse, cargo transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalVesselUse Context triple: [Walter L. Frost shipwreck, hasOriginalVesselUse, cargo transport]
-
A.
hasVessel
Indicates that one entity possesses, uses, or is associated with a particular vessel (such as a container, ship, or transport medium) in the context of the described relationship or action.
-
B.
usesVesselType
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
C.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
D.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
-
E.
originallyHad
chosen
Indicates that an entity previously possessed, contained, or was associated with something before a change, loss, or transformation occurred.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb5f85d48190ba80a0a24fbe438a |
completed | March 9, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69aef900386481909d04555a9ec9b0e3 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.