Triple
T27468296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnston Center for Integrative Studies |
E693237
|
entity |
| Predicate | livingLearningModel |
P162419
|
FINISHED |
| Object | residential program where most students live together |
—
|
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: residential program where most students live together | Statement: [Johnston Center for Integrative Studies, livingLearningModel, residential program where most students live together]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: livingLearningModel Context triple: [Johnston Center for Integrative Studies, livingLearningModel, residential program where most students live together]
-
A.
educationalModel
Indicates that one entity serves as an educational model, framework, or paradigm that guides or structures the teaching, learning, or training practices of another entity.
-
B.
learn
Indicates that an entity acquires knowledge, skills, or understanding from another entity, source, or experience.
-
C.
usesLearningMechanism
Indicates that one entity employs or applies a particular learning mechanism or method in its functioning or behavior.
-
D.
learningModel
Indicates that one entity functions as a learning model used to learn from data or examples in relation to another entity.
-
E.
structureLearning
Indicates a process in which an agent infers or constructs the underlying structure or dependency relationships within a set of variables, data, or a model.
- F. None of above. chosen
Provenance (4 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_69ef538105548190a771cc5a0cf8c211 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f62dfe6f7881909a45a89d1b753b1a |
completed | May 2, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f624c006788190a2f4d5015c96463f |
completed | May 2, 2026, 4:22 p.m. |
Created at: April 27, 2026, 12:53 p.m.