Triple
T17996756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2006 Czech legislative election |
E430520
|
entity |
| Predicate | numberOfPartiesInChamber |
P130061
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [2006 Czech legislative election, numberOfPartiesInChamber, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPartiesInChamber Context triple: [2006 Czech legislative election, numberOfPartiesInChamber, 5]
-
A.
numberOfLegislativeChambers
Indicates the quantity of distinct legislative chambers that a given political or legislative body possesses.
-
B.
hasLegislativeChamberSeats
Indicates that a legislative chamber holds or is allocated a specified number of seats.
-
C.
largestPartySeatCount
Indicates the number of seats held by the single largest party in a legislative or representative body.
-
D.
numberOfCommitteeMembers
Indicates the total count of individuals who are members of a given committee.
-
E.
numberOfSupportVotesInChamber
Indicates the count of votes cast in favor of a proposal within a specific legislative chamber.
- F. None of above. chosen
Provenance (4 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b3e4ae948190903ed255b0fe1dca |
completed | April 19, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:23 a.m.