Triple
T12748190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oliveira Salazar |
E304659
|
entity |
| Predicate | replacedInOfficeDueTo |
P56544
|
FINISHED |
| Object | illness |
—
|
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: illness | Statement: [Oliveira Salazar, replacedInOfficeDueTo, illness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replacedInOfficeDueTo Context triple: [Oliveira Salazar, replacedInOfficeDueTo, illness]
-
A.
replacedInOffice
Indicates that one officeholder succeeded and took over the official position previously held by another.
-
B.
replacedOffice
Indicates that one office or position has been succeeded or taken over by another, replacing it in its former role or function.
-
C.
placedBy
Indicates that one entity was positioned, set, or put in a location or context by another entity.
-
D.
replacedBecause
chosen
Indicates that one entity has been substituted for another specifically due to a particular reason or cause.
-
E.
replacesOffice
Indicates that one office takes over the role, function, or position previously held by another office.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:27 p.m.