Triple
T38029345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Concordia College New York |
E948863
|
entity |
| Predicate | campusPropertyAcquiredBy |
P189878
|
FINISHED |
| Object | Iona College |
—
|
NE NERFINISHED |
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: Iona College | Statement: [Concordia College New York, campusPropertyAcquiredBy, Iona College]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusPropertyAcquiredBy Context triple: [Concordia College New York, campusPropertyAcquiredBy, Iona College]
-
A.
hasCampusOn
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
-
B.
campusOwner
Indicates that one entity owns, controls, or is responsible for a particular campus.
-
C.
campusName
Indicates the official name assigned to a particular campus.
-
D.
campusUsedBy
Indicates that a particular campus is utilized or occupied by a specified group, organization, or set of entities.
-
E.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
- 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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc993caa881908c16c3e21efaeef9 |
completed | May 6, 2026, 11:07 p.m. |
Created at: May 3, 2026, 4:20 p.m.