Triple
T24430229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa Lachey |
E615981
|
entity |
| Predicate | militaryBrat |
P156090
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Vanessa Lachey, militaryBrat, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryBrat Context triple: [Vanessa Lachey, militaryBrat, true]
-
A.
militaryBranchEmphasis
Indicates a relationship where a military branch is given particular focus, priority, or specialization within a broader military or organizational context.
-
B.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
C.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military organization.
-
D.
derivedFromMilitaryOrCivil
Indicates that something originates from, is based on, or is obtained through military or civil (non-military governmental) sources, activities, or contexts.
-
E.
isMilitarySchool
Indicates that an educational institution functions as a military school, operating under military principles, structure, or training programs.
- 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_69e2d7eadb248190a867130fe45f0388 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296aab8948190b9cb869bab71fb4c |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:15 a.m.