Triple
T36684555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Aveiro |
E905780
|
entity |
| Predicate | legalStatusAfterScandal |
P201120
|
FINISHED |
| Object | attainted |
—
|
LITERAL FINISHED |
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: attainted | Statement: [Duke of Aveiro, legalStatusAfterScandal, attainted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusAfterScandal Context triple: [Duke of Aveiro, legalStatusAfterScandal, attainted]
-
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.
reputationBeforeScandal
Indicates the reputation or public standing an entity had prior to a specific scandal or damaging event.
-
D.
rescuedFromScandalBy
Indicates that one party’s reputation or situation was saved or rehabilitated from a scandal through the actions or intervention of another party.
-
E.
disgracedFor
Indicates that an entity has lost honor, respect, or status specifically because of the associated reason, action, or circumstance.
- F. None of above. chosen
Provenance (4 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffc89596d08190b97bd60b45c7f9c0 |
completed | May 9, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69ffc81ba5dc8190ae94d44e2284948f |
completed | May 9, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ffc894cef481908dae1d9cdc7d9d1f |
completed | May 9, 2026, 11:51 p.m. |
Created at: May 3, 2026, 4:12 p.m.