Triple
T378239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Assembly of Zimbabwe |
E8617
|
entity |
| Predicate | hasYouthQuotaSeats |
P9399
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [National Assembly of Zimbabwe, hasYouthQuotaSeats, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasYouthQuotaSeats Context triple: [National Assembly of Zimbabwe, hasYouthQuotaSeats, 10]
-
A.
hasReservedSeats
chosen
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
-
B.
hasClubSeats
Indicates that an entity (such as a venue or section) includes or is equipped with club-level seating.
-
C.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
D.
hasElectionFraction
Indicates that a specified portion or fraction of the total vote or electorate is associated with a particular election-related entity or outcome.
-
E.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given entity.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2974988190a1d6316cbb5159c8 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96351cc8190a55adf95f8c27e9e |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.