Triple
T28776626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Bertram |
E726549
|
entity |
| Predicate | guardianAfterScandal |
P28704
|
FINISHED |
| Object | Aunt Norris |
—
|
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: Aunt Norris | Statement: [Maria Bertram, guardianAfterScandal, Aunt Norris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: guardianAfterScandal Context triple: [Maria Bertram, guardianAfterScandal, Aunt Norris]
-
A.
effectOfScandal
Indicates the consequences or impact that a particular scandal has on a person, organization, event, or situation.
-
B.
associatedScandal
Indicates a relationship where an entity is linked to, involved in, or notably connected with a particular scandal.
-
C.
guardian
chosen
Indicates a protective or custodial relationship in which one entity is responsible for the care, safety, or oversight of another.
-
D.
timeOfMajorScandal
Indicates the specific time period during which a major scandal involving the entity occurred.
-
E.
reputationBeforeScandal
Indicates the reputation or public standing an entity had prior to a specific scandal or damaging event.
- 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f658ee40088190b71e1219407690d0 |
completed | May 2, 2026, 8:05 p.m. |
| PD | Predicate disambiguation | batch_69f65760fd3081908ffe014a5e2bf069 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 6:18 a.m.