Triple
T181551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plessy v. Ferguson |
E3886
|
entity |
| Predicate | typeOfSegregation |
P3951
|
FINISHED |
| Object | de jure racial segregation |
—
|
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: de jure racial segregation | Statement: [Plessy v. Ferguson, typeOfSegregation, de jure racial segregation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSegregation Context triple: [Plessy v. Ferguson, typeOfSegregation, de jure racial segregation]
-
A.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
-
B.
divisionTitle
Indicates the formal name or title assigned to a specific division within a larger organization or structure.
-
C.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
D.
typeOfJurisdiction
Indicates the specific kind or category of legal authority or control that one jurisdiction holds in relation to a given legal or administrative context.
-
E.
demarcationType
chosen
Indicates the specific way in which a boundary or separation between entities is defined, marked, or categorized.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25923507c8190bd7f6eda404b0da0 |
completed | Feb. 28, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69a2566ccc288190add5624ede96d82b |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.