Triple
T28684252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant General Walter C. Short |
E726086
|
entity |
| Predicate | consequenceOfMeasures |
P812
|
FINISHED |
| Object | aircraft were vulnerable to surprise air attack |
—
|
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: aircraft were vulnerable to surprise air attack | Statement: [Lieutenant General Walter C. Short, consequenceOfMeasures, aircraft were vulnerable to surprise air attack]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consequenceOfMeasures Context triple: [Lieutenant General Walter C. Short, consequenceOfMeasures, aircraft were vulnerable to surprise air attack]
-
A.
consequenceOfPolicies
Indicates the outcomes or effects that result from the implementation or existence of specific policies.
-
B.
consequenceOfInfluence
Indicates that one event, state, or condition occurs as a result of the influence or impact exerted by another.
-
C.
hasConsequence
chosen
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
D.
consequenceOfReforms
Indicates that something occurs as a result of, or is caused by, a set of reforms.
-
E.
consequenceOfApplication
Indicates that something occurs as a result or outcome of a particular application or use of something.
- 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_69f01d867608819086bc3e6b4f9de866 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6bbf6e33c819086e5176d64e7a614 |
completed | May 3, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
Created at: April 28, 2026, 5:11 a.m.