Triple
T10504932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimbabwean general election, 2000 |
E247761
|
entity |
| Predicate | totalSeatsInParliament |
P73787
|
FINISHED |
| Object | 150 |
—
|
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: 150 | Statement: [Zimbabwean general election, 2000, totalSeatsInParliament, 150]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalSeatsInParliament Context triple: [Zimbabwean general election, 2000, totalSeatsInParliament, 150]
-
A.
parliamentarySeats
Indicates the number of seats a party, group, or representative holds in a parliamentary body.
-
B.
numberOfSeatsInHouseOfCommons
Indicates the total count of seats allocated in the House of Commons.
-
C.
hasLegislativeChamberSeats
chosen
Indicates that a legislative chamber holds or is allocated a specified number of seats.
-
D.
legislativeAssemblySeats
Indicates the number of seats an entity holds or is allocated in a legislative assembly.
-
E.
numberOfHousesInParliament
Indicates the count of distinct legislative chambers that make up a country's parliament.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099f4dec8190a9851739c8bc9a69 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:26 p.m.