Triple
T1617315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yale Law School |
E34748
|
entity |
| Predicate | admissionsRate |
P738
|
FINISHED |
| Object | single-digit percentage |
—
|
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: single-digit percentage | Statement: [Yale Law School, admissionsRate, single-digit percentage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: admissionsRate Context triple: [Yale Law School, admissionsRate, single-digit percentage]
-
A.
admissionsLevel
Indicates the degree or category of access, entry, or acceptance granted in an admissions context.
-
B.
admissionType
Indicates the category or manner in which an entity (such as a person or case) is formally accepted or admitted into a system, institution, or process.
-
C.
hasAdmission
Indicates that an entity possesses or is associated with a specific admission event, record, or status (such as being admitted to a place, program, or institution).
-
D.
admissionDate
Indicates the date on which an entity (such as a person, application, or item) is formally admitted, accepted, or entered into a system or institution.
-
E.
typicalAdmissionSelectivity
chosen
Indicates the usual level of competitiveness or restrictiveness in admitting applicants to an institution or program.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fef600c819080fe75c42c8e6dac |
completed | March 5, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69a907c52a548190b648a31ea306dd5b |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.