Triple
T3261693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ron Rivera |
E68424
|
entity |
| Predicate | militaryBackgroundInFamily |
P13742
|
FINISHED |
| Object | United States Army family |
—
|
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: United States Army family | Statement: [Ron Rivera, militaryBackgroundInFamily, United States Army family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryBackgroundInFamily Context triple: [Ron Rivera, militaryBackgroundInFamily, United States Army family]
-
A.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
B.
hasFamilyBackgroundIn
chosen
Indicates that an entity comes from, or is associated with, a particular familial or ancestral background.
-
C.
hasMilitaryBranch
Indicates that an entity is associated with, served in, or is part of a specific branch of a military organization.
-
D.
hadMilitaryObligationsTo
Indicates that one party was bound by duty or law to provide military service, support, or protection to another party.
-
E.
placeOfMilitaryService
Indicates the location or institution where a person performed their military 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafa7fea08190b089b6174fd7cd32 |
completed | March 8, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69ada41d7eac8190ada4bf5f793d5c49 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.