Triple
T709251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewis & Clark College |
E14169
|
entity |
| Predicate | admissionsType |
P738
|
FINISHED |
| Object | selective |
—
|
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: selective | Statement: [Lewis & Clark College, admissionsType, selective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: admissionsType Context triple: [Lewis & Clark College, admissionsType, selective]
-
A.
undergraduateIntakeType
Indicates the specific category or mode by which undergraduate students are admitted or enrolled into an academic program or institution.
-
B.
typicalAdmissionSelectivity
chosen
Indicates the usual level of competitiveness or restrictiveness in admitting applicants to an institution or program.
-
C.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
D.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
E.
applicantType
Indicates the classification or category of an applicant in relation to an application or selection process.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5c011948190b2cfccd8fe722742 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f0217081908268b3f47e72f8df |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.