Triple
T1996235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niña |
E43364
|
entity |
| Predicate | approximateTonnage |
P7301
|
FINISHED |
| Object | about 60 tons |
—
|
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 60 tons | Statement: [Niña, approximateTonnage, about 60 tons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTonnage Context triple: [Niña, approximateTonnage, about 60 tons]
-
A.
tonnage
Indicates the relationship between an object and the measure of its weight or cargo capacity, typically expressed in tons.
-
B.
approximateMass
chosen
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another entity.
-
C.
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.
-
D.
tonnageClass
Indicates a classification relationship where an entity is assigned to a category based on its tonnage (weight or carrying capacity range).
-
E.
grossTonnage
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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb91055d88190a980e7b42e5895d4 |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb79c97d48190b3147430ed39faa9 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.