Triple
T21447323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCaslin plantation |
E529109
|
entity |
| Predicate | hasHistoricalBackstory |
P1409
|
FINISHED |
| Object | antebellum slave plantation |
—
|
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: antebellum slave plantation | Statement: [McCaslin plantation, hasHistoricalBackstory, antebellum slave plantation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalBackstory Context triple: [McCaslin plantation, hasHistoricalBackstory, antebellum slave plantation]
-
A.
hasFictionalBackstory
Indicates that an entity is associated with an invented or imaginary narrative background rather than a real-world history.
-
B.
expandsBackstoryOf
Indicates that one entity provides additional background details or context that elaborate on the history or origins of another entity.
-
C.
hasLongHistory
Indicates that the relationship or subject has existed or persisted over a long period of time.
-
D.
hasHistoricalContext
chosen
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
-
E.
hasHistoricalOrigin
Indicates that something originated, was first established, or came into existence during a specific historical period or context.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d04548819086594c20faa5217d |
completed | April 23, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:06 p.m.