Triple
T26134129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Catharine plantation, Charles County, Maryland |
E659328
|
entity |
| Predicate | linkedToOccupationOfOwner |
P38273
|
FINISHED |
| Object | physician |
—
|
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: physician | Statement: [St. Catharine plantation, Charles County, Maryland, linkedToOccupationOfOwner, physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToOccupationOfOwner Context triple: [St. Catharine plantation, Charles County, Maryland, linkedToOccupationOfOwner, physician]
-
A.
ownerOccupation
chosen
Indicates that the occupation or job role of an entity that owns something is being specified or described.
-
B.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
C.
occupationOfAssociatedPerson
Indicates the job or professional role held by a person who is associated with another referenced entity.
-
D.
holderIsOccupation
Indicates that the holder entity has the specified occupation or job role.
-
E.
ownershipBasedIn
Indicates that an entity’s ownership or controlling stake is primarily located, registered, or based in a particular place or jurisdiction.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 26, 2026, 8:16 p.m.