Triple
T27916844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel, United States Marine Corps Reserve |
E706096
|
entity |
| Predicate | typicalCivilianRole |
P117349
|
FINISHED |
| Object | maintains civilian career |
—
|
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: maintains civilian career | Statement: [Colonel, United States Marine Corps Reserve, typicalCivilianRole, maintains civilian career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCivilianRole Context triple: [Colonel, United States Marine Corps Reserve, typicalCivilianRole, maintains civilian career]
-
A.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
B.
civilianResponse
Indicates how civilians react or respond to a particular event, action, or situation.
-
C.
isCivilian
Indicates that an entity is a non-military, non-combatant individual in the context of a given situation or system.
-
D.
typicalAdditionalRole
chosen
Indicates that an entity commonly or characteristically holds an extra role or function in addition to its primary one.
-
E.
civilianVariant
Indicates that one entity is a civilian version or non-military counterpart of another entity.
- 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_69ef96b6cc808190aab19fb18b235f4b |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_6a0039c2d5d48190b8ef2c7ef17d8dc5 |
completed | May 10, 2026, 7:54 a.m. |
| PD | Predicate disambiguation | batch_6a0038e525448190a4c815f51595e78d |
completed | May 10, 2026, 7:51 a.m. |
Created at: April 27, 2026, 6:54 p.m.