Triple
T27261505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Widener University |
E687776
|
entity |
| Predicate | hasPredecessorInstitution |
P3528
|
FINISHED |
| Object | Bullock School |
—
|
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: Bullock School | Statement: [Widener University, hasPredecessorInstitution, Bullock School]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPredecessorInstitution Context triple: [Widener University, hasPredecessorInstitution, Bullock School]
-
A.
hasFormerInstitution
Indicates that an entity was previously affiliated with, employed by, or enrolled in a particular institution in the past.
-
B.
hasFormerInstitutionType
Indicates that an entity was previously associated with or classified under a particular type of institution.
-
C.
hasFormerInstitutionName
Indicates that an institution was previously known by a different name.
-
D.
parentInstitutionFormerName
Indicates that the parent institution of an entity previously operated under a different official name.
-
E.
successorInstitution
chosen
Indicates that one institution continues, replaces, or takes over the role and functions of another institution in a successor relationship.
- 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_69ef3557abc481908bf3c146f0f3356a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fdd07a34c08190982b8c61c2775cf6 |
completed | May 8, 2026, noon |
| PD | Predicate disambiguation | batch_69fdbd25c7908190b72fca8de7ce503f |
completed | May 8, 2026, 10:38 a.m. |
Created at: April 27, 2026, 10:53 a.m.