Triple
T2993602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Virginia State Board of Education v. Barnette |
E81012
|
entity |
| Predicate | defendantClass |
P2238
|
FINISHED |
| Object | Jehovah's Witness schoolchildren |
—
|
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: Jehovah's Witness schoolchildren | Statement: [West Virginia State Board of Education v. Barnette, defendantClass, Jehovah's Witness schoolchildren]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defendantClass Context triple: [West Virginia State Board of Education v. Barnette, defendantClass, Jehovah's Witness schoolchildren]
-
A.
defendant
chosen
Indicates that an entity is the party accused or sued in a legal action or proceeding.
-
B.
coDefendant
Indicates that two or more parties are jointly named and involved as defendants in the same legal case or proceeding.
-
C.
defendantStatus
Indicates the legal condition or standing of a defendant within a judicial or law-enforcement process.
-
D.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given context.
-
E.
defendantsNationality
Indicates that the specified nationality is attributed to the defendants in a legal case.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99e291e0819089f81c0a7d7a6cd9 |
completed | March 8, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ad961403108190bbecb8d3608fd4e0 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.