Triple
T806015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump family |
E17434
|
entity |
| Predicate | politicalOfficeHeldByMember |
P16080
|
FINISHED |
| Object | President of the United States |
—
|
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: President of the United States | Statement: [Trump family, politicalOfficeHeldByMember, President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalOfficeHeldByMember Context triple: [Trump family, politicalOfficeHeldByMember, President of the United States]
-
A.
memberHoldsOffice
chosen
Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
-
B.
alsoHoldsOfficeOf
Indicates that an entity currently holding one office or position simultaneously holds another office or position as well.
-
C.
electedOffice
Indicates that an entity holds or has held a particular office or position as a result of an election.
-
D.
hasMemberOfParliament
Indicates that an entity is represented by a specific individual serving as its Member of Parliament.
-
E.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ace495348190aec66f35ea90bc89 |
completed | March 1, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69a4aa70973c8190adbf08302d1103a9 |
completed | March 1, 2026, 9:06 p.m. |
Created at: March 1, 2026, 7:38 p.m.