Triple
T29895829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WE Charity |
E759274
|
entity |
| Predicate | controversyInvolvedPerson |
P190792
|
FINISHED |
| Object | Justin Trudeau |
—
|
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: Justin Trudeau | Statement: [WE Charity, controversyInvolvedPerson, Justin Trudeau]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controversyInvolvedPerson Context triple: [WE Charity, controversyInvolvedPerson, Justin Trudeau]
-
A.
roleInControversy
Indicates the specific part, involvement, or function an entity has within a particular controversy or disputed situation.
-
B.
controversyType
Indicates the specific kind or category of controversy associated with an entity or situation.
-
C.
implicatedPerson
chosen
Indicates that a person is alleged or shown to be involved in, responsible for, or connected to a particular event, action, or wrongdoing.
-
D.
controversialBecause
Indicates that one entity is considered controversial specifically due to, or as a result of, its relationship with or association to another entity.
-
E.
marriagePartnerOfControversialFigure
Indicates that one entity is the spouse of a figure who is widely regarded as controversial.
- 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_69f2245f1cf88190978c70d1a1d2cb73 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: April 29, 2026, 6:04 p.m.