Triple
T1067861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria (ship) |
E23253
|
entity |
| Predicate | tonnage |
P24299
|
FINISHED |
| Object | about 85 tons burden |
—
|
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: about 85 tons burden | Statement: [Victoria (ship), tonnage, about 85 tons burden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tonnage Context triple: [Victoria (ship), tonnage, about 85 tons burden]
-
A.
grossTonnage
Indicates the total internal volume or carrying capacity of a vessel, measured in gross tons, as defined by maritime tonnage rules.
-
B.
deadweightTonnage
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.
-
C.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
-
D.
weight
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
-
E.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
- 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b9e1047481909af1cf8df2a01fff |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b736f1e881909bace735b38c0ade |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b9df0a308190a0d87dcd8afe58bc |
completed | March 1, 2026, 10:12 p.m. |
Created at: March 1, 2026, 7:42 p.m.