Triple
T2457219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Braxton Bragg |
E54449
|
entity |
| Predicate | postMilitaryCareer |
P40607
|
FINISHED |
| Object | civil engineer |
—
|
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: civil engineer | Statement: [Braxton Bragg, postMilitaryCareer, civil engineer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postMilitaryCareer Context triple: [Braxton Bragg, postMilitaryCareer, civil engineer]
-
A.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
B.
postMilitaryUse
Indicates that an entity is used or repurposed after its original military function or service has ended.
-
C.
placeOfMilitaryService
Indicates the location or institution where a person performed their military service.
-
D.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
E.
militaryStatus
Indicates the relationship between an entity and a military organization in terms of service condition, such as active duty, reserve, veteran, or non-military status.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd49b5d2481908817aeb171e2bd61 |
completed | March 7, 2026, 7:32 a.m. |
Created at: March 6, 2026, 9:44 p.m.