Triple
T3965760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gratz v. Bollinger |
E92212
|
entity |
| Predicate | programTypeChallenged |
P2192
|
FINISHED |
| Object | undergraduate admissions point system |
—
|
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: undergraduate admissions point system | Statement: [Gratz v. Bollinger, programTypeChallenged, undergraduate admissions point system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programTypeChallenged Context triple: [Gratz v. Bollinger, programTypeChallenged, undergraduate admissions point system]
-
A.
programChallenged
Indicates that one entity has formally questioned, disputed, or sought to overturn a program, plan, or initiative associated with another entity.
-
B.
programType
chosen
Indicates the category or kind of program to which an entity belongs or with which it is associated.
-
C.
mayBeChallengedBy
Indicates that one entity is allowed or able to be opposed, questioned, or contested by another entity.
-
D.
challengeType
Indicates the specific category or kind of challenge associated with an action or relationship between entities.
-
E.
hasChallenge
Indicates that an entity faces, experiences, or is confronted with a particular difficulty, obstacle, or problem.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefba878a48190a2e234d775215938 |
completed | March 9, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69aef8efcf3c81908ccf61d9ce26b0c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:32 p.m.