Triple
T1836194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacqueline du Pré |
E41071
|
entity |
| Predicate | reasonForEndOfCareer |
P10984
|
FINISHED |
| Object | multiple sclerosis |
—
|
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: multiple sclerosis | Statement: [Jacqueline du Pré, reasonForEndOfCareer, multiple sclerosis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForEndOfCareer Context triple: [Jacqueline du Pré, reasonForEndOfCareer, multiple sclerosis]
-
A.
reasonForLeaving
Indicates the cause, motivation, or circumstance that led an entity to depart or discontinue an association, position, or place.
-
B.
reasonForEndOfTerm
Indicates the specific cause or circumstance that led to the termination or conclusion of a term, position, or period of service.
-
C.
typeOfOccupationEnded
Indicates that a particular type of occupation or job role has come to an end for an entity.
-
D.
reasonForDiscontinuation
Indicates that one entity specifies the cause or justification for stopping, ending, or withdrawing another entity, process, or activity.
-
E.
causeOfEarlyRetirement
chosen
Indicates that one entity is the reason or contributing factor leading another entity to retire earlier than the typical or expected time.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafd88ebc81908208394746351fe6 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.