Triple
T26601779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle off Fort Nelson |
E667654
|
entity |
| Predicate | EnglishShip |
P3345
|
FINISHED |
| Object | Hudson's Bay Company ship Dering |
—
|
NE NERFINISHED |
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: Hudson's Bay Company ship Dering | Statement: [Battle off Fort Nelson, EnglishShip, Hudson's Bay Company ship Dering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EnglishShip Context triple: [Battle off Fort Nelson, EnglishShip, Hudson's Bay Company ship Dering]
-
A.
BritishShipRate
Indicates that the subject is classified or rated according to the British naval ship rating system (e.g., first-rate, second-rate, etc.).
-
B.
approximateEnglishShips
Indicates that one entity is an estimated or approximate count of English ships associated with another entity or context.
-
C.
shipsOfTheLine
Indicates a relationship where the associated entities are classified as ships of the line, i.e., major warships designed to participate in the main line of battle.
-
D.
FrenchShipType
Indicates that something is classified as a type of ship associated with France, such as by origin, design, or service.
-
E.
notableShip
chosen
Indicates that there is a notable or significant ship associated with the subject entity.
- 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_69ee9cfd20348190bb1255d2603efb7a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620debeb48190b7db395fb86cf8d9 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 2:12 a.m.