Triple
T2480610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince-Archbishopric of Mainz |
E55804
|
entity |
| Predicate | rankInElectoralCollege |
P39748
|
FINISHED |
| Object | presiding elector |
—
|
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: presiding elector | Statement: [Prince-Archbishopric of Mainz, rankInElectoralCollege, presiding elector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInElectoralCollege Context triple: [Prince-Archbishopric of Mainz, rankInElectoralCollege, presiding elector]
-
A.
electoralVotesReceived
Indicates that one entity received a specified number of electoral votes in an election from another entity or jurisdiction.
-
B.
electoralVotesWinner
Indicates that the subject is the candidate who received the highest number of electoral votes in a given election.
-
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.
numberOfElectors
Indicates the total count of electors associated with a given entity or context.
-
E.
electoralVotesNeededToWin
Indicates the minimum number of electoral votes a candidate must obtain in an election to be declared the winner.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd1eb3be481908fa7c6b8f1c78209 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b5e3d481909a5cbc4a96edd24f |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1e45380819094b3f32a278bd457 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:45 p.m.