Triple
T36166839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernst Robinson |
E1046026
|
entity |
| Predicate | occupationBeforeShipwreck |
P135155
|
FINISHED |
| Object | student |
—
|
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: student | Statement: [Ernst Robinson, occupationBeforeShipwreck, student]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationBeforeShipwreck Context triple: [Ernst Robinson, occupationBeforeShipwreck, student]
-
A.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
B.
survivorOccupation
chosen
Indicates that the person is a survivor and specifies the occupation they held (typically at or around the time of the event they survived).
-
C.
resumedOccupation
Indicates that an entity has returned to and continued a previous occupation or role after a period of interruption or absence.
-
D.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
E.
victimOccupation
Indicates the profession or job role held by the person who is the victim in an event or incident.
- 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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:08 p.m.