Triple
T435217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiberius |
E9795
|
entity |
| Predicate | militaryCampaign |
P710
|
FINISHED |
| Object | campaigns in Germania |
—
|
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: campaigns in Germania | Statement: [Tiberius, militaryCampaign, campaigns in Germania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryCampaign Context triple: [Tiberius, militaryCampaign, campaigns in Germania]
-
A.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
B.
majorWar
Indicates a large-scale, intense armed conflict between major powers or involving substantial military forces and widespread impact.
-
C.
militaryTheater
chosen
Indicates that an entity is a geographic or operational area where military operations or campaigns are conducted.
-
D.
warfareType
Indicates the specific kind or category of warfare that characterizes a given conflict or military engagement.
-
E.
militaryStrategy
Indicates a relationship where an entity plans, directs, or is associated with the organized use of armed forces and tactics to achieve military or defense objectives.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ef0b6e0c8190ad6a335ee804829c |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2edda55e88190b7c17ba94d7df1ce |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.