Triple
T33845153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimbabwean parliamentary election, 1995 |
E867459
|
entity |
| Predicate | totalSeatsInHouseOfAssembly |
P96187
|
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 parliamentary election, 1995, totalSeatsInHouseOfAssembly, 150]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalSeatsInHouseOfAssembly Context triple: [Zimbabwean parliamentary election, 1995, totalSeatsInHouseOfAssembly, 150]
-
A.
numberOfSeatsInHouseOfCommons
Indicates the total count of seats allocated in the House of Commons.
-
B.
parliamentarySeatsTotal
chosen
Indicates the total number of seats in a given parliament or parliamentary body.
-
C.
hasLegislativeChamberSeats
Indicates that a legislative chamber holds or is allocated a specified number of seats.
-
D.
numberOfHousesInParliament
Indicates the count of distinct legislative chambers that make up a country's parliament.
-
E.
legislativeAssemblySeats
Indicates the number of seats an entity holds or is allocated in a legislative assembly.
- 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_69f349937b648190a34ada70f6a2b534 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 1, 2026, 1:47 a.m.