Triple
T1992186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angela |
E43274
|
entity |
| Predicate | hasWorkplaceRole |
P13957
|
FINISHED |
| Object | management |
—
|
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: management | Statement: [Angela, hasWorkplaceRole, management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkplaceRole Context triple: [Angela, hasWorkplaceRole, management]
-
A.
hasOrganizationalRole
chosen
Indicates that an entity holds a specific role, position, or function within an organization.
-
B.
hasPositionInOrganization
Indicates that an entity holds a specific role, job, or position within a particular organization.
-
C.
hasContactRole
Indicates that an entity serves in a specific role or capacity as a contact for another entity.
-
D.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.