Triple
T5482936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Lieutenant of Shropshire |
E123507
|
entity |
| Predicate | scopeOfVisits |
P64296
|
FINISHED |
| Object | royal engagements within Shropshire |
—
|
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: royal engagements within Shropshire | Statement: [Lord Lieutenant of Shropshire, scopeOfVisits, royal engagements within Shropshire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scopeOfVisits Context triple: [Lord Lieutenant of Shropshire, scopeOfVisits, royal engagements within Shropshire]
-
A.
visits
Indicates that one entity goes to or spends time at the location or presence of another entity.
-
B.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
C.
numberOfAnnualPatientVisits
Indicates the total count of patient visits that occur over the course of one year.
-
D.
hasVisitation
Indicates that one entity visits, or is allowed or scheduled to visit, another entity or location.
-
E.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited by another entity.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd93e5d0f08190a6cc9fc408b7c5bb |
completed | March 20, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69bd91a73b148190a865243536a4fe76 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd93e4d2d081908eb75ee22fe72824 |
completed | March 20, 2026, 6:37 p.m. |
Created at: March 20, 2026, 2:09 p.m.