Triple
T35828055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Creighton University |
E1035706
|
entity |
| Predicate | hasNamesakeBenefactor |
P16661
|
FINISHED |
| Object | Mary Heider |
—
|
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: Mary Heider | Statement: [Creighton University, hasNamesakeBenefactor, Mary Heider]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamesakeBenefactor Context triple: [Creighton University, hasNamesakeBenefactor, Mary Heider]
-
A.
hasPhilanthropicOrganizationNamedAfter
Indicates that an entity has a philanthropic organization that is named after it.
-
B.
notablePhilanthropicBeneficiary
Indicates that an entity is a significant recipient of philanthropic donations, support, or charitable contributions from another entity.
-
C.
philanthropicBeneficiary
chosen
Indicates that one entity is the recipient or target of another entity’s philanthropic giving or charitable support.
-
D.
hasPhilanthropicFounder
Indicates that an entity has a founder who is actively engaged in philanthropy or charitable giving.
-
E.
hasFamousNamesake
Indicates that an entity shares its name with another well-known or notable entity.
- 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_69f76e192a94819082db360cb91e6a8d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff63225b6481909217ad11b4f7d3ba |
completed | May 9, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69ff60e0882c819085d097010db43ee0 |
completed | May 9, 2026, 4:29 p.m. |
Created at: May 3, 2026, 4:06 p.m.