Triple
T9852237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Hansen |
E239494
|
entity |
| Predicate | reasonForEndOfService |
P6707
|
FINISHED |
| Object | retirement due to health reasons |
—
|
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: retirement due to health reasons | Statement: [Christian Hansen, reasonForEndOfService, retirement due to health reasons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForEndOfService Context triple: [Christian Hansen, reasonForEndOfService, retirement due to health reasons]
-
A.
reasonForDiscontinuation
Indicates that one entity specifies the cause or justification for stopping, ending, or withdrawing another entity, process, or activity.
-
B.
reasonForEndOfTerm
chosen
Indicates the specific cause or circumstance that led to the termination or conclusion of a term, position, or period of service.
-
C.
reasonForEndOfMission
Indicates the cause or circumstance that led to the termination or conclusion of a mission.
-
D.
originalServiceEnded
Indicates that a previously existing or initial service has come to an end or has been terminated.
-
E.
inactivationReason
Indicates the reason or cause for which an entity, status, or process has been deactivated or made inactive.
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb375ba448190a32cca2b0f376ac1 |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:34 p.m.