Triple
T2843259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rider University |
E62518
|
entity |
| Predicate | knownForProgram |
P10900
|
FINISHED |
| Object | business |
—
|
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: business | Statement: [Rider University, knownForProgram, business]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForProgram Context triple: [Rider University, knownForProgram, business]
-
A.
alsoKnownFor
Indicates that an entity is additionally recognized or noted for another work, role, achievement, or characteristic beyond its primary association.
-
B.
refersToPersonKnownFor
Indicates that one entity makes reference to a person who is notable or recognized for some specific role, achievement, or characteristic.
-
C.
notableProgramInvolvement
chosen
Indicates that an entity has a significant or distinguished role or participation in a particular program.
-
D.
underlyingKnownFor
Indicates that one entity is fundamentally or primarily recognized as the basis or main reason for another entity’s notability or fame.
-
E.
knownForSports
Indicates that an entity is recognized or notable for its involvement, achievement, or association with sports.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf1a07508190be35fe85733ddeed |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd0e86808190bcefffafbd3cd441 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:01 p.m.