Triple
T2416934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Médaille militaire |
E52325
|
entity |
| Predicate | hasCivilianClass |
P37793
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Médaille militaire, hasCivilianClass, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCivilianClass Context triple: [Médaille militaire, hasCivilianClass, false]
-
A.
isCivilian
Indicates that an entity is a non-military, non-combatant individual in the context of a given situation or system.
-
B.
isCivilianOffice
Indicates that an office or position is non-military and belongs to the civilian sphere of authority or administration.
-
C.
isCivilianAward
Indicates that an award is designated for civilians rather than military or combat-related recipients.
-
D.
accuracyCivilianTypical
Indicates the degree to which something typically achieves accurate results or effects when applied to civilians.
-
E.
hasCivilianControl
Indicates that one party exercises authority or oversight over another in a civilian (non-military) capacity.
- 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc94eafd481909eeff689e5bf5960 |
completed | March 7, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_69abc5a6cbd0819086c0716e266b7ebb |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6011e348190b6f9c038c7559289 |
completed | March 7, 2026, 6:30 a.m. |
Created at: March 6, 2026, 9:42 p.m.