Triple
T1755083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Lieutenant of Cornwall |
E38531
|
entity |
| Predicate | officeContingentOn |
P32786
|
FINISHED |
| Object | pleasure of the Crown |
—
|
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: pleasure of the Crown | Statement: [Lord Lieutenant of Cornwall, officeContingentOn, pleasure of the Crown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeContingentOn Context triple: [Lord Lieutenant of Cornwall, officeContingentOn, pleasure of the Crown]
-
A.
officeInvolved
Indicates that a particular office or organizational unit is involved or participates in a specified event, action, or relationship.
-
B.
includedOffice
Indicates that one office is contained within, or forms part of, another office or organizational unit.
-
C.
officeContested
Indicates that a particular office or position is being actively sought or challenged by multiple parties in an election or selection process.
-
D.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
E.
officeIsIn
Indicates that one office is located within or inside another specified place or building.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba6a63f588190b53b39c6b97d74f4 |
completed | March 7, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_69aa61c7ef4c8190abec87c96a787d82 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aba6a4c84c8190b3ce0bf69c2b5f6d |
completed | March 7, 2026, 4:16 a.m. |
Created at: March 4, 2026, 7:31 p.m.