Triple
T752837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regents of the University of California v. Bakke |
E15486
|
entity |
| Predicate | quotaDescription |
P11875
|
FINISHED |
| Object | 16 of 100 seats reserved for minority applicants |
—
|
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: 16 of 100 seats reserved for minority applicants | Statement: [Regents of the University of California v. Bakke, quotaDescription, 16 of 100 seats reserved for minority applicants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quotaDescription Context triple: [Regents of the University of California v. Bakke, quotaDescription, 16 of 100 seats reserved for minority applicants]
-
A.
describedIn
Indicates that information about an entity is contained or documented within a specified source, such as a text, document, or media.
-
B.
hasDescription
chosen
Indicates that an entity is associated with a textual description that explains or characterizes it.
-
C.
describes
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
-
D.
symbolDescription
Indicates that a symbol is associated with or defined by a particular descriptive explanation or meaning.
-
E.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64d7d2c8190a6059adcb8fbd34f |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a501c4cc81908de6d63e3d4f60d7 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.