Triple
T4749426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Washington’s tomb at Mount Vernon |
E105440
|
entity |
| Predicate | hasVisitorPractice |
P5308
|
FINISHED |
| Object | wreath-laying ceremonies |
—
|
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: wreath-laying ceremonies | Statement: [George Washington’s tomb at Mount Vernon, hasVisitorPractice, wreath-laying ceremonies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisitorPractice Context triple: [George Washington’s tomb at Mount Vernon, hasVisitorPractice, wreath-laying ceremonies]
-
A.
hasVisitation
Indicates that one entity visits, or is allowed or scheduled to visit, another entity or location.
-
B.
hasTypeOfVisitorExperience
chosen
Indicates that an entity is associated with a particular category or kind of visitor experience it provides or involves.
-
C.
hasVisitorServices
Indicates that an entity provides services or facilities specifically intended for visitors or guests.
-
D.
hasVisitorPolicy
Indicates that an entity has an established policy governing the presence, behavior, or permissions of visitors.
-
E.
hasVisitorType
Indicates the type or category of visitor associated with an entity (e.g., guest, customer, tourist, patient).
- 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_69bd43f07fa48190954317d01600994a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64c6f5ac81908a62f9c17e77ac86 |
completed | March 20, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69bd6223defc8190823665a6592c1154 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.