Triple
T15506162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mabel Thayer Mahoney |
E379086
|
entity |
| Predicate | sponsoredVesselType |
P118913
|
FINISHED |
| Object | heavy cruiser |
—
|
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: heavy cruiser | Statement: [Mabel Thayer Mahoney, sponsoredVesselType, heavy cruiser]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsoredVesselType Context triple: [Mabel Thayer Mahoney, sponsoredVesselType, heavy cruiser]
-
A.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
-
B.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
C.
sponsoredVoyagesOf
Indicates that one entity provided financial or logistical support for the voyages undertaken by another entity.
-
D.
usesVesselType
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
E.
shipSponsor
Indicates that one entity serves as the sponsor or patron responsible for supporting, endorsing, or funding a particular ship.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcd5d948190b25a67a72ef980e9 |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2896a9c8190a8b9627deb3c17b4 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57165288190979b7acb71ad5145 |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:55 a.m.