Triple
T36284812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (1973) |
E893046
|
entity |
| Predicate | tonnageType |
P19645
|
FINISHED |
| Object | gross register tonnage |
—
|
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: gross register tonnage | Statement: [SS Empress of Britain (1973), tonnageType, gross register tonnage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tonnageType Context triple: [SS Empress of Britain (1973), tonnageType, gross register tonnage]
-
A.
tonnageClass
Indicates a classification relationship where an entity is assigned to a category based on its tonnage (weight or carrying capacity range).
-
B.
tonnage
Indicates the relationship between an object and the measure of its weight or cargo capacity, typically expressed in tons.
-
C.
tonnageGrossRegisterTonsApproximate
Indicates that the gross register tonnage of something (typically a vessel) is given as an approximate value rather than an exact measurement.
-
D.
typeOfHaulage
Indicates the kind or category of haulage service or transport operation associated with an entity.
-
E.
grossTonnage
chosen
Indicates the total internal volume or carrying capacity of a vessel, measured in gross tons, as defined by maritime tonnage rules.
- 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_69f76e4955c08190b8cfddca34fc0242 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.