Triple
T34909841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jester Clane |
E1006833
|
entity |
| Predicate | associatedWithWorkSetting |
P205605
|
FINISHED |
| Object | segregated American South |
—
|
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: segregated American South | Statement: [Jester Clane, associatedWithWorkSetting, segregated American South]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithWorkSetting Context triple: [Jester Clane, associatedWithWorkSetting, segregated American South]
-
A.
associatedWithInWork
Indicates that two entities are connected or related to each other within the context of a particular work or project.
-
B.
associatedWithWorkforce
Indicates a relationship in which an entity is connected or related to a particular workforce, such as its members, activities, or management.
-
C.
associatedWithWorkplace
Indicates a relationship where an entity has a connection or affiliation with a particular workplace or place of employment.
-
D.
associatedWithWorkOf
Indicates that one entity has a connection or involvement with the work, creation, or output produced by another entity.
-
E.
associatedWorkType
Indicates the type or category of work with which an entity is associated (e.g., publication, artwork, performance).
- F. None of above. chosen
Provenance (4 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_69f76dc1b4a081909b4c6e4d8ec0aa2d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.