Triple
T8181851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sister Bodily Death |
E191080
|
entity |
| Predicate | hasThematicRelationTo |
P49998
|
FINISHED |
| Object | mortality |
—
|
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: mortality | Statement: [Sister Bodily Death, hasThematicRelationTo, mortality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThematicRelationTo Context triple: [Sister Bodily Death, hasThematicRelationTo, mortality]
-
A.
hasThematicConcern
Indicates that one entity (such as a work, text, or discourse) centrally involves, addresses, or focuses on a particular theme, issue, or subject as a primary concern.
-
B.
majorThemeAssociation
chosen
Indicates that one entity is associated with another as a primary or central theme.
-
C.
hasSubjectThesaurus
Indicates that an entity is associated with or described using a particular subject thesaurus or controlled subject vocabulary.
-
D.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
E.
followsInTheme
Indicates that one element continues or succeeds another while maintaining the same theme or thematic context.
- 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_69ca82c4538081909404325aa5639483 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c4db8748190aa785e0c70fac497 |
completed | March 31, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69cb36a7952481908f34e3e82f375a84 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:40 p.m.