Triple
T3684418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Ivies |
E78188
|
entity |
| Predicate | termUsage |
P2529
|
FINISHED |
| Object | primarily used in college admissions discourse |
—
|
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: primarily used in college admissions discourse | Statement: [Little Ivies, termUsage, primarily used in college admissions discourse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termUsage Context triple: [Little Ivies, termUsage, primarily used in college admissions discourse]
-
A.
usedTerm
Indicates that one entity employed, referenced, or applied a particular term in some context.
-
B.
titleUsage
Indicates how a title is applied, referenced, or used in relation to an entity or context.
-
C.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
D.
termAlsoUsedFor
Indicates that one term is also used to refer to the same or closely related concept as another term.
-
E.
brandUsage
Indicates that one entity uses, features, or is associated with another entity’s brand in its products, services, or communications.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc49644d08190866d6c5df9d2b48d |
completed | March 8, 2026, 6:48 p.m. |
| PD | Predicate disambiguation | batch_69adb84be1fc81909721c871babb4633 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:26 p.m.