Triple
T26394049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Alexandre Beck |
E663497
|
entity |
| Predicate | subjectOfMessages |
P166147
|
FINISHED |
| Object | Elizabeth Beck may still be alive |
—
|
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: Elizabeth Beck may still be alive | Statement: [Dr. Alexandre Beck, subjectOfMessages, Elizabeth Beck may still be alive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectOfMessages Context triple: [Dr. Alexandre Beck, subjectOfMessages, Elizabeth Beck may still be alive]
-
A.
subjectKey
Indicates that the subject serves as a unique key or identifier used to reference or distinguish an entity in a relationship or dataset.
-
B.
titleSubjectOf
Indicates that a title (such as a book, article, or work) is about or primarily concerns a particular subject.
-
C.
subjectImpliedAs
Indicates that the subject of an action or statement is not explicitly stated but is understood or inferred from context.
-
D.
subjectMVP
Indicates that the subject is considered the most valuable player (MVP) in a given context or event.
-
E.
subjectOfIntroduction
Indicates that one entity is the topic or focus being introduced by another entity.
- 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_69ee883823988190b418b111be28a44a |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f66003a3f48190a2ba6da5aafbb5cb |
completed | May 2, 2026, 8:35 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
| PDg | Predicate description generation | batch_69f65f75ac608190a62cd6afce14f68e |
completed | May 2, 2026, 8:32 p.m. |
Created at: April 26, 2026, 11:27 p.m.