Triple
T37985761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gulf Coast theatre of the American Revolutionary War |
E947682
|
entity |
| Predicate | involvedOperationType |
P1137
|
FINISHED |
| Object | land warfare |
—
|
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: land warfare | Statement: [Gulf Coast theatre of the American Revolutionary War, involvedOperationType, land warfare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedOperationType Context triple: [Gulf Coast theatre of the American Revolutionary War, involvedOperationType, land warfare]
-
A.
notableOperationType
Indicates that an entity is associated with a specific type or category of operation that is considered notable or significant.
-
B.
typeOfOperation
Indicates the specific kind or category of operation being performed or referenced in a given context.
-
C.
associatedOperation
Indicates that one entity is linked to or involved with a particular operation, process, or activity.
-
D.
operationType
Indicates the specific kind of operation or action being performed or recorded in the relationship between entities.
-
E.
hasOperationType
chosen
Indicates the specific kind or category of operation associated with an entity or process.
- 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_69f76ef8a1d08190a741bbbc5970e3b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69feced53a7c819098ec474fb7d514b0 |
completed | May 9, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69fecd9cd5288190aac8b4e04a7ee78e |
completed | May 9, 2026, 6:01 a.m. |
Created at: May 3, 2026, 4:20 p.m.