Triple
T26069165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard family tomb, High Park, Toronto |
E657492
|
entity |
| Predicate | benefactorOfSite |
P33009
|
FINISHED |
| Object | John George Howard |
—
|
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: John George Howard | Statement: [Howard family tomb, High Park, Toronto, benefactorOfSite, John George Howard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefactorOfSite Context triple: [Howard family tomb, High Park, Toronto, benefactorOfSite, John George Howard]
-
A.
benefactor
Indicates that one entity provides help, support, or resources to another, typically in a generous or supportive role.
-
B.
philanthropicBeneficiary
Indicates that one entity is the recipient or target of another entity’s philanthropic giving or charitable support.
-
C.
benefactionLocation
Indicates the place or location where a benefaction (such as a gift, donation, or helpful act) is given, received, or takes effect.
-
D.
beneficiaryContribution
Indicates that one party provides a contribution, support, or resources that benefit another designated beneficiary.
-
E.
funderOf
chosen
Indicates that one entity provides financial support or funding for another entity, project, or activity.
- 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_69ee5bbe539081909efc7f9dd7c1b53c |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f606c91710819081f3e0187820f1e8 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 7:27 p.m.