Triple
T1806470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the Senate of Zimbabwe |
E40230
|
entity |
| Predicate | officeHolderMust |
P2718
|
FINISHED |
| Object | be a member of the Senate |
—
|
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: be a member of the Senate | Statement: [President of the Senate of Zimbabwe, officeHolderMust, be a member of the Senate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderMust Context triple: [President of the Senate of Zimbabwe, officeHolderMust, be a member of the Senate]
-
A.
officeHoldersMustBe
chosen
Indicates that individuals who hold a particular office are required to possess a specified status, qualification, or characteristic.
-
B.
officeHolderMayBe
Indicates that a specified person is permitted or eligible to hold a particular office or position.
-
C.
officeHoldersMustNot
Indicates that certain individuals are prohibited from holding specified offices or positions.
-
D.
officeHolderUsually
Indicates that an entity is the person who typically or customarily holds a particular office or position.
-
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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d514c081908197ac1f7c7d7a88 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.