Triple
T34678004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Czechoslovak parliamentary election of 1935 |
E890542
|
entity |
| Predicate | largestPartySeatsChamberOfDeputies |
P122316
|
FINISHED |
| Object | 44 |
—
|
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: 44 | Statement: [Czechoslovak parliamentary election of 1935, largestPartySeatsChamberOfDeputies, 44]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestPartySeatsChamberOfDeputies Context triple: [Czechoslovak parliamentary election of 1935, largestPartySeatsChamberOfDeputies, 44]
-
A.
largestPartySeatCount
chosen
Indicates the number of seats held by the single largest party in a legislative or representative body.
-
B.
largestParty
Indicates that the subject is the political party with the greatest size (e.g., by membership, seats, or votes) within a specified context or group.
-
C.
numberOfPartiesInChamber
Indicates the total count of distinct parties represented within a specific legislative chamber.
-
D.
secondLargestPartySeatsWon
Indicates the number of seats won by the political party that finished second in size or vote share in an election.
-
E.
wonMostChamberOfDeputiesSeats
Indicates that an entity secured the highest number of seats in the Chamber of Deputies in a given election or time period.
- 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_69f349dabc008190a18999c26682ed47 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f728a345488190bd7e6751b09ac591 |
completed | May 3, 2026, 10:51 a.m. |
| PD | Predicate disambiguation | batch_69f7283ef2608190a7a85d7e7f5332c0 |
completed | May 3, 2026, 10:49 a.m. |
Created at: May 1, 2026, 2:05 a.m.