Triple
T26778704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | July 25, 2019 Trump–Zelenskyy phone call |
E670190
|
entity |
| Predicate | officeHeldByParticipant |
P127364
|
FINISHED |
| Object | Donald Trump was 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: Donald Trump was President of the United States | Statement: [July 25, 2019 Trump–Zelenskyy phone call, officeHeldByParticipant, Donald Trump was President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldByParticipant Context triple: [July 25, 2019 Trump–Zelenskyy phone call, officeHeldByParticipant, Donald Trump was President of the United States]
-
A.
officeHeldByActor
chosen
Indicates that a specific office, position, or role is held or occupied by a particular actor.
-
B.
officeHeldByMember
Indicates that a specific office or position is held or occupied by a particular member.
-
C.
officeHeldByMembers
Indicates that a particular office or position is held by one or more members of a specified group or organization.
-
D.
officeHeldDuring
Indicates that a person occupied a specific official position during a particular time period.
-
E.
officeHeldWithNumber
Indicates that an entity holds a specific office or position together with an associated ordinal or numerical designation (e.g., first term, second office number).
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: April 27, 2026, 4:07 a.m.