Triple
T28926418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nate Getz |
E733658
|
entity |
| Predicate | fictionalOrganizationMembership |
P109189
|
FINISHED |
| Object | Naval Criminal Investigative Service |
—
|
NE NERFINISHED |
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: Naval Criminal Investigative Service | Statement: [Nate Getz, fictionalOrganizationMembership, Naval Criminal Investigative Service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalOrganizationMembership Context triple: [Nate Getz, fictionalOrganizationMembership, Naval Criminal Investigative Service]
-
A.
setInFictionalOrganization
Indicates that an entity is located within, associated with, or takes place inside a fictional organization.
-
B.
worksForFictionalOrganization
chosen
Indicates that an entity is employed by or affiliated as a worker with a fictional organization.
-
C.
appearsInOrganization
Indicates that an entity is present, featured, or participates within a particular organization.
-
D.
organizationInStory
Indicates that an organization appears or plays a role within the context of a specific story.
-
E.
fictionalOrganizationFeatured
Indicates that a fictional organization is prominently presented or plays a significant role within a given work or context.
- 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_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: April 28, 2026, 8:23 a.m.