Triple
T782832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Electorate of Cologne |
E16534
|
entity |
| Predicate | temporalLeader |
P4208
|
FINISHED |
| Object | Prince-Archbishop of Cologne |
—
|
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: Prince-Archbishop of Cologne | Statement: [Electorate of Cologne, temporalLeader, Prince-Archbishop of Cologne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalLeader Context triple: [Electorate of Cologne, temporalLeader, Prince-Archbishop of Cologne]
-
A.
leaderSince
Indicates that an entity has held a leadership role over another entity starting from a specified point in time.
-
B.
hasLeader
Indicates that one entity serves as the leader or head of another entity.
-
C.
leaderDuring
chosen
Indicates that one entity serves as the leader of another entity during a specified time period.
-
D.
namedByLeader
Indicates that an entity has been given its name by a specific leader or person in authority.
-
E.
hasFormerLeader
Indicates that an entity previously held the role of leader of another entity but no longer does.
- 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.