Triple
T17109406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women’s Royal Naval Service |
E415184
|
entity |
| Predicate | allowedSeaService |
P125972
|
FINISHED |
| Object | no, primarily shore-based |
—
|
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: no, primarily shore-based | Statement: [Women’s Royal Naval Service, allowedSeaService, no, primarily shore-based]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allowedSeaService Context triple: [Women’s Royal Naval Service, allowedSeaService, no, primarily shore-based]
-
A.
usesAtSea
Indicates that something is employed, operated, or applied in a maritime or oceanic environment.
-
B.
appliesToSeaArea
Indicates that something (such as a rule, restriction, or designation) is relevant or valid within a specified sea area.
-
C.
navalAccess
Indicates that one entity has the right or ability to use another entity’s naval facilities, waters, or maritime routes for military or strategic purposes.
-
D.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
-
E.
maritimeActivity
Indicates activities, operations, or behaviors that take place at sea or are directly related to maritime environments and navigation.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc29c884819092a97d9663a1b1f7 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:35 a.m.