Triple
T2103946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Rumyantsev |
E37150
|
entity |
| Predicate | typeOfOffensive |
P25454
|
FINISHED |
| Object | summer offensive |
—
|
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: summer offensive | Statement: [Operation Rumyantsev, typeOfOffensive, summer offensive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfOffensive Context triple: [Operation Rumyantsev, typeOfOffensive, summer offensive]
-
A.
offense
Indicates that one entity commits, causes, or is responsible for a violation, wrongdoing, or rule-breaking act against another entity or governing norms.
-
B.
usedOffensiveSystem
Indicates that an entity employed an offensive system (such as a weapon or attack mechanism) against another entity or target.
-
C.
offenseNicknamed
Indicates that an offensive unit, team, or strategy is commonly referred to by a particular nickname.
-
D.
hasTypeOfViolence
Indicates that an entity involves, exhibits, or is characterized by a specific kind or category of violent behavior or action.
-
E.
offensiveStrategy
chosen
Indicates a strategic approach focused on attacking or aggressively advancing against an opponent.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbabf7cdc81909636dff34badc1c5 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7b7b6288190afa11b4d93bd5666 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.