Triple
T3856029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria (ship) |
E90015
|
entity |
| Predicate | partOfFleetSize |
P1848
|
FINISHED |
| Object | 5 ships at departure |
—
|
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: 5 ships at departure | Statement: [Victoria (ship), partOfFleetSize, 5 ships at departure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfFleetSize Context triple: [Victoria (ship), partOfFleetSize, 5 ships at departure]
-
A.
fleetSize
chosen
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
B.
squadronSize
Indicates the number of units or members that make up a particular squadron.
-
C.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
D.
hasSubfleet
Indicates that one fleet entity contains or manages another fleet entity as a subordinate or component fleet.
-
E.
fleetIncludes
Indicates that a particular fleet contains or is composed of the specified entity or entities as its members.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec07d45081909b8f3e35eb710f4c |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.