Triple
T4504352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1935 United Kingdom general election |
E101295
|
entity |
| Predicate | totalSeatsContested |
P11588
|
FINISHED |
| Object | 615 |
—
|
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: 615 | Statement: [1935 United Kingdom general election, totalSeatsContested, 615]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalSeatsContested Context triple: [1935 United Kingdom general election, totalSeatsContested, 615]
-
A.
numberOfSeatsContested
chosen
Indicates the total count of seats in an election or contest that are being competed for or are up for selection.
-
B.
numberOfSeatsWon
Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
-
C.
numberOfNoContests
Indicates the total count of events, matches, or decisions that were recorded as "no contest" rather than a win, loss, or draw.
-
D.
numberOfCandidates
Indicates the total count of candidates associated with a given entity or context.
-
E.
hasOfficeContested
Indicates that an individual has been a candidate for a particular public office in an election.
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56fe17608190ae5dc27052b7c337 |
completed | March 20, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69bd521671688190bc655d25fa77eba2 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:01 p.m.