Triple
T18327361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1949 Australian federal election |
E439045
|
entity |
| Predicate | expandedSenateSeatsTo |
P48166
|
FINISHED |
| Object | 60 |
—
|
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: 60 | Statement: [1949 Australian federal election, expandedSenateSeatsTo, 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expandedSenateSeatsTo Context triple: [1949 Australian federal election, expandedSenateSeatsTo, 60]
-
A.
numberOfSeatsInSenate
chosen
Indicates the total count of seats allocated in a given senate.
-
B.
numberOfSenates
Indicates the total count of senate bodies associated with or present in a given context or entity.
-
C.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
-
D.
numberOfSenators
Indicates the total count of senators associated with a given political body, region, or entity.
-
E.
numberOfAtLargeSeats
Indicates the total count of at-large seats (positions not tied to specific districts or subunits) associated with an 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aac14488190840b9c22209f13d1 |
completed | April 19, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.