Triple
T26522453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montevideo Maru |
E669993
|
entity |
| Predicate | tonnageGrossRegisterTonsApproximate |
P160604
|
FINISHED |
| Object | about 7053 |
—
|
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 7053 | Statement: [Montevideo Maru, tonnageGrossRegisterTonsApproximate, about 7053]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tonnageGrossRegisterTonsApproximate Context triple: [Montevideo Maru, tonnageGrossRegisterTonsApproximate, about 7053]
-
A.
grossTonnage
Indicates the total internal volume or carrying capacity of a vessel, measured in gross tons, as defined by maritime tonnage rules.
-
B.
tonnage
Indicates the relationship between an object and the measure of its weight or cargo capacity, typically expressed in tons.
-
C.
tonnageClass
Indicates a classification relationship where an entity is assigned to a category based on its tonnage (weight or carrying capacity range).
-
D.
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.
-
E.
maxVesselTonnage
Indicates the maximum tonnage capacity that a vessel is allowed or designed 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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f613c35b5481909ef85d87d1604be9 |
completed | May 2, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69f602d7b1b0819095ddd3b5169f8ce2 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f6037bf7a081908862a8359be80cf8 |
completed | May 2, 2026, 2 p.m. |
Created at: April 27, 2026, 1:29 a.m.