Triple
T36861029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Canada (2038) |
E910935
|
entity |
| Predicate | hasTonnage |
P19646
|
FINISHED |
| Object | unknown |
—
|
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: unknown | Statement: [SS Empress of Canada (2038), hasTonnage, unknown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTonnage Context triple: [SS Empress of Canada (2038), hasTonnage, unknown]
-
A.
tonnage
Indicates the relationship between an object and the measure of its weight or cargo capacity, typically expressed in tons.
-
B.
estimatedMassInTonnes
Indicates the approximate mass of an entity expressed in metric tonnes.
-
C.
slingLoadCapacity
Indicates the maximum weight or load that can be safely carried or supported using a sling.
-
D.
tonnageClass
Indicates a classification relationship where an entity is assigned to a category based on its tonnage (weight or carrying capacity range).
-
E.
deadweightTonnage
chosen
Indicates the total carrying capacity of a vessel, measured as the maximum weight of cargo, fuel, passengers, provisions, and other loads it can safely transport.
- 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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: May 3, 2026, 4:13 p.m.