Triple
T18665247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Mont-Blanc |
E456306
|
entity |
| Predicate | typeOfCargoShip |
P3141
|
FINISHED |
| Object | munitions transport |
—
|
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: munitions transport | Statement: [SS Mont-Blanc, typeOfCargoShip, munitions transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCargoShip Context triple: [SS Mont-Blanc, typeOfCargoShip, munitions transport]
-
A.
typeOfMediumship
Indicates a relationship where one entity specifies the particular form or method of mediumship practiced or involved in relation to another entity.
-
B.
shipClass
chosen
Indicates the classification or type category to which a particular ship belongs.
-
C.
shipTypeProduced
Indicates that a particular type of ship is produced, built, or manufactured by a given entity.
-
D.
tonnageClass
Indicates a classification relationship where an entity is assigned to a category based on its tonnage (weight or carrying capacity range).
-
E.
laterShipType
Indicates that one ship type chronologically succeeds or is introduced after another ship type.
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5508e02788190bdea6099f08db4f0 |
completed | April 19, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69e478db7a248190a8c6584673773923 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:48 a.m.