Triple
T34189418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelby plantation |
E877056
|
entity |
| Predicate | hasInhabitantClassInFiction |
P97696
|
FINISHED |
| Object | enslaved people |
—
|
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: enslaved people | Statement: [Shelby plantation, hasInhabitantClassInFiction, enslaved people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInhabitantClassInFiction Context triple: [Shelby plantation, hasInhabitantClassInFiction, enslaved people]
-
A.
hasSpeciesInFiction
Indicates that a fictional work or universe features a particular species as part of its narrative or setting.
-
B.
hasFictionalGenreCharacteristic
Indicates that something possesses a specific characteristic or attribute related to a fictional genre.
-
C.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another entity.
-
D.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
E.
hasFictionalInhabitants
chosen
Indicates that a place or setting is inhabited by fictional or imaginary beings.
- 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_69f349af20a4819089ac24d28f2d8112 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a00144238708190acbec3f791cc873e |
completed | May 10, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_6a00120244a4819090ef39070aba9d99 |
completed | May 10, 2026, 5:05 a.m. |
Created at: May 1, 2026, 1:55 a.m.