Triple
T10238109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Tyler monument |
E243518
|
entity |
| Predicate | memorializedPersonRole |
P4096
|
FINISHED |
| Object | President of the United States |
—
|
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: President of the United States | Statement: [John Tyler monument, memorializedPersonRole, President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memorializedPersonRole Context triple: [John Tyler monument, memorializedPersonRole, President of the United States]
-
A.
memorialRole
Indicates that an entity holds a specific role, capacity, or function in relation to a memorial or commemorative context.
-
B.
commemoratedPerson
Indicates that the subject serves as a memorial or tribute to the referenced person.
-
C.
commemoratesRoleAs
chosen
Indicates that something serves to honor or recognize a specific role or position held by an entity.
-
D.
memorialName
Indicates that a memorial is known by or designated with a particular name.
-
E.
commemoratedFor
Indicates that one entity is honored, remembered, or celebrated because of a particular action, achievement, event, or characteristic associated with it.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:23 a.m.