Triple
T786656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strategic Services Unit |
E16816
|
entity |
| Predicate | employedTypeOfPersonnel |
P11881
|
FINISHED |
| Object | intelligence analysts |
—
|
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: intelligence analysts | Statement: [Strategic Services Unit, employedTypeOfPersonnel, intelligence analysts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employedTypeOfPersonnel Context triple: [Strategic Services Unit, employedTypeOfPersonnel, intelligence analysts]
-
A.
personnelType
chosen
Indicates the classification or role category assigned to a person within an organization or system.
-
B.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
C.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
D.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
E.
hasWorkforceType
Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a77fcc6881908a025bb21e44ad56 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:38 p.m.