Triple
T7349557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonas Melcher |
E169460
|
entity |
| Predicate | spouseNotableAncestorOccupation |
P4765
|
FINISHED |
| Object | naturalist |
—
|
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: naturalist | Statement: [Jonas Melcher, spouseNotableAncestorOccupation, naturalist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseNotableAncestorOccupation Context triple: [Jonas Melcher, spouseNotableAncestorOccupation, naturalist]
-
A.
spouseNotableFor
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
B.
spouseNotableWorkField
Indicates that the notable work or professional field associated with a person’s spouse is being specified.
-
C.
spouseOccupation
chosen
Indicates that one person’s spouse has a particular job, profession, or occupation.
-
D.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
E.
spouseRoleInHistory
Indicates that one entity serves or is recognized as the spouse of another entity within a specific historical context or period.
- 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f139505c8190a7158cf59a6e089e |
completed | March 27, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69c6f02aeeb8819099d1626566cec18b |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:05 p.m.