Triple
T6731623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dereliction of Duty |
E153645
|
entity |
| Predicate | placesInQuestion |
P73412
|
FINISHED |
| Object | effectiveness of U.S. high-level decision-making in war |
—
|
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: effectiveness of U.S. high-level decision-making in war | Statement: [Dereliction of Duty, placesInQuestion, effectiveness of U.S. high-level decision-making in war]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placesInQuestion Context triple: [Dereliction of Duty, placesInQuestion, effectiveness of U.S. high-level decision-making in war]
-
A.
placesWithin
Indicates that one place or area is located entirely inside the boundaries of another place or area.
-
B.
placesInContext
Indicates that one entity situates, interprets, or frames another entity within a particular context or surrounding circumstances.
-
C.
placeType
Indicates the type or category of place associated with an entity (e.g., city, park, building).
-
D.
placeOfInquiry
Indicates the location or institution where a question, investigation, or request for information is directed or conducted.
-
E.
placeDescribed
Indicates that one entity provides a description or account of a particular place or location.
- F. None of above. chosen
Provenance (4 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d35134148190b49fb5c25a0f8ed4 |
completed | March 27, 2026, 6:58 p.m. |
Created at: March 27, 2026, 2:09 p.m.