Triple
T3678002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of the Chesapeake |
E78041
|
entity |
| Predicate | shipsInvolvedApprox |
P861
|
FINISHED |
| Object | 24 French ships of the line |
—
|
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: 24 French ships of the line | Statement: [Battle of the Chesapeake, shipsInvolvedApprox, 24 French ships of the line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipsInvolvedApprox Context triple: [Battle of the Chesapeake, shipsInvolvedApprox, 24 French ships of the line]
-
A.
numberOfShipsInvolved
chosen
Indicates the total count of ships that participated or were involved in a specified event or situation.
-
B.
shipInvolved
Indicates that a ship participates in, is associated with, or plays a role in a specified event or situation.
-
C.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
D.
shipTypeInvolved
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
-
E.
navalForceInvolved
Indicates that a naval military force participates in, contributes to, or is otherwise involved in a specified event or operation.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc46599188190a046eddb0d85c483 |
completed | March 8, 2026, 6:48 p.m. |
| PD | Predicate disambiguation | batch_69adb84be1fc81909721c871babb4633 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.