Triple
T32158952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varner–Hogg Plantation |
E821373
|
entity |
| Predicate | interpretsTopic |
P165591
|
FINISHED |
| Object | plantation economy |
—
|
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: plantation economy | Statement: [Varner–Hogg Plantation, interpretsTopic, plantation economy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interpretsTopic Context triple: [Varner–Hogg Plantation, interpretsTopic, plantation economy]
-
A.
intendedInterpretation
Indicates that one entity is meant to be understood or interpreted in a particular way, sense, or meaning relative to another.
-
B.
includesTopics
Indicates that one entity contains, covers, or addresses the specified topics as part of its content or scope.
-
C.
topicOfDiscourse
chosen
Indicates that something serves as the subject or focus of a particular discussion, conversation, or communicative act.
-
D.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
-
E.
PSATopic
Indicates that one entity serves as the subject, theme, or focus of a public service announcement related to the other entity.
- 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_69f34905e098819082191a6922a6d607 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
Created at: May 1, 2026, 12:32 a.m.