Triple
T13612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European theatre of World War II |
E274
|
entity |
| Predicate | conflictType |
P1397
|
FINISHED |
| Object | major front of World War II |
—
|
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: major front of World War II | Statement: [European theatre of World War II, conflictType, major front of World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictType Context triple: [European theatre of World War II, conflictType, major front of World War II]
-
A.
conflictSide
Indicates that an entity participates as a distinct party or faction on one side of a conflict or dispute.
-
B.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
C.
officeContested
Indicates that a particular office or position is being actively sought or challenged by multiple parties in an election or selection process.
-
D.
typeOfContract
Indicates the specific kind or category of contractual agreement that applies between the related entities.
-
E.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a243abb2ec8190937365e5ecec52ad |
completed | Feb. 28, 2026, 1:23 a.m. |
| PD | Predicate disambiguation | batch_69a23fe9470c8190918a6ca1df168646 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a243aa85848190813154e8a6495200 |
completed | Feb. 28, 2026, 1:23 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.