Triple
T14906436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Primrose Shipman |
E360142
|
entity |
| Predicate | spouseConviction |
P55300
|
FINISHED |
| Object | murder |
—
|
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: murder | Statement: [Primrose Shipman, spouseConviction, murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseConviction Context triple: [Primrose Shipman, spouseConviction, murder]
-
A.
spouseExecutedFor
Indicates that one person’s spouse was put to death, typically as a result of a legal or punitive execution.
-
B.
spouseInvolvedIn
chosen
Indicates that a person's spouse participates in, is associated with, or plays a role in a specified activity, event, or situation.
-
C.
spouseExecuted
Indicates that one person’s spouse was put to death, typically as a result of a legal or extrajudicial execution.
-
D.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded60cd5588190b1efecc2b220da69 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:12 a.m.