Triple
T28927568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mallory Grennan |
E733690
|
entity |
| Predicate | postMilitaryLife |
P40607
|
FINISHED |
| Object | civilian life in the United States |
—
|
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: civilian life in the United States | Statement: [Mallory Grennan, postMilitaryLife, civilian life in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postMilitaryLife Context triple: [Mallory Grennan, postMilitaryLife, civilian life in the United States]
-
A.
postMilitaryCareer
chosen
Indicates that one entity’s career or occupation occurs after the completion of their military service.
-
B.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military organization.
-
C.
postMilitaryUse
Indicates that an entity is used or repurposed after its original military function or service has ended.
-
D.
postMilitaryName
Indicates the name or designation an entity holds after completing or leaving military service.
-
E.
retiredFromUSMilitary
Indicates that an individual previously served in the United States military and has formally ended their military career or service.
- 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_69f05b0b49b08190b8994b339c7980f6 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65b4fee008190bc43ed7e719872db |
completed | May 2, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:25 a.m.