Triple
T782824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Electorate of Cologne |
E16534
|
entity |
| Predicate | electorNumber |
P16492
|
FINISHED |
| Object | one of seven prince-electors |
—
|
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: one of seven prince-electors | Statement: [Electorate of Cologne, electorNumber, one of seven prince-electors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electorNumber Context triple: [Electorate of Cologne, electorNumber, one of seven prince-electors]
-
A.
numberOfElectors
chosen
Indicates the total count of electors associated with a given entity or context.
-
B.
increasedNumberOfElectors
Indicates that the number of electors associated with an entity has grown compared to a previous state or reference point.
-
C.
hasElectoralVotes
Indicates that a political entity (such as a state or district) possesses a specified number of votes in an electoral system used to choose an officeholder.
-
D.
electionNumber
Indicates the specific ordinal or identifying number assigned to a particular election within a series or system of elections.
-
E.
electoralVotesWinner
Indicates that the subject is the candidate who received the highest number of electoral votes in a given 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7686d0881908c2a4395059be02c |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.