Triple
T76109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altmark Incident |
E1520
|
entity |
| Predicate | typeOfAction |
P819
|
FINISHED |
| Object | naval boarding operation |
—
|
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: naval boarding operation | Statement: [Altmark Incident, typeOfAction, naval boarding operation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAction Context triple: [Altmark Incident, typeOfAction, naval boarding operation]
-
A.
typeOfOperation
chosen
Indicates the specific kind or category of operation being performed or referenced in a given context.
-
B.
operationType
Indicates the specific kind of operation or action being performed or recorded in the relationship between entities.
-
C.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given context.
-
D.
typeOfContract
Indicates the specific kind or category of contractual agreement that applies between the related entities.
-
E.
decisionType
Indicates the specific category or nature of a decision associated with an entity or 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.