Triple
T742651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Combat Infantryman Badge |
E15275
|
entity |
| Predicate | conflictSpecific |
P18893
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Combat Infantryman Badge, conflictSpecific, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictSpecific Context triple: [Combat Infantryman Badge, conflictSpecific, yes]
-
A.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
B.
conflictType
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
C.
mainConflict
Indicates the primary opposing force, problem, or struggle that drives tension and narrative progression between entities or sides.
-
D.
conflictContext
Indicates the situational background or circumstances within which a conflict between entities occurs or is interpreted.
-
E.
conflictBelligerent
Indicates that an entity is a participating belligerent (e.g., a country, group, or force) in a specific conflict.
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a60f92d08190a4f44c5b4d068ab5 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fdaaf48190985f62acfc069508 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a5a35c68819082429755c046e9a7 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:37 p.m.