Triple
T14966940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boynton v. Virginia |
E373213
|
entity |
| Predicate | segregatedFacilityType |
P11398
|
FINISHED |
| Object | restaurant in a bus terminal |
—
|
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: restaurant in a bus terminal | Statement: [Boynton v. Virginia, segregatedFacilityType, restaurant in a bus terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: segregatedFacilityType Context triple: [Boynton v. Virginia, segregatedFacilityType, restaurant in a bus terminal]
-
A.
designedFacilityType
Indicates the type or category of facility that something (such as a plan, system, or component) is specifically designed for.
-
B.
fccFacilityType
Indicates the specific type or classification of a facility as defined by the FCC (Federal Communications Commission).
-
C.
typeOfSegregationAddressed
chosen
Indicates the specific form or category of segregation that is being targeted, handled, or dealt with in a given context.
-
D.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
E.
typeOfSeparation
Indicates the specific manner or category of separation that exists or occurred between entities.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e2fdcc8190bffe603db3388736 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:47 a.m.