Triple
T12065883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Lawrence |
E287293
|
entity |
| Predicate | casualtiesInBattleOfLakeErie |
P35438
|
FINISHED |
| Object | high casualties |
—
|
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: high casualties | Statement: [USS Lawrence, casualtiesInBattleOfLakeErie, high casualties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesInBattleOfLakeErie Context triple: [USS Lawrence, casualtiesInBattleOfLakeErie, high casualties]
-
A.
casualtiesAtTannenberg
Indicates that the entities are related through casualties that occurred during the Battle of Tannenberg.
-
B.
statusDuringBattleOfPlattsburgh
Indicates the role, condition, or situation an entity held specifically during the Battle of Plattsburgh.
-
C.
casualties_British_side
Indicates the number or extent of casualties suffered by the British side in a conflict or incident.
-
D.
casualtiesDescription
Indicates a textual description of the human losses (such as deaths, injuries, or missing persons) resulting from an event or incident.
-
E.
casualtiesAssociatedWithEvent
chosen
Indicates that certain casualties (deaths or injuries) are linked to, or resulted from, a specific event.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.