Triple
T36656002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Gonda |
E904989
|
entity |
| Predicate | hasBuildingNamedAfter |
P49744
|
FINISHED |
| Object | Gonda Building at Mayo Clinic |
—
|
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: Gonda Building at Mayo Clinic | Statement: [Leslie Gonda, hasBuildingNamedAfter, Gonda Building at Mayo Clinic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingNamedAfter Context triple: [Leslie Gonda, hasBuildingNamedAfter, Gonda Building at Mayo Clinic]
-
A.
hasBuildingNamedAfterHim
chosen
Indicates that a person has a building that is named in their honor.
-
B.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
-
C.
hasHeritageSiteNamedAfter
Indicates that one entity has a heritage site that is named after another entity.
-
D.
hasCapitalNamedAfter
Indicates that one entity serves as the capital of another entity and that this capital is named after the other entity.
-
E.
hasParkNamedAfter
Indicates that one entity has a park that is named in honor of, or after, another 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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: May 3, 2026, 4:11 p.m.