Triple
T13518111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosa Hubermann |
E322819
|
entity |
| Predicate | showsAffectionThrough |
P23414
|
FINISHED |
| Object | practical care |
—
|
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: practical care | Statement: [Rosa Hubermann, showsAffectionThrough, practical care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showsAffectionThrough Context triple: [Rosa Hubermann, showsAffectionThrough, practical care]
-
A.
hasAffectionateUse
Indicates that one entity uses or refers to another in a loving, tender, or emotionally warm manner.
-
B.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
C.
emotionallyAttachedTo
chosen
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another entity.
-
D.
attitudeTowardLove
Indicates an entity’s feelings, beliefs, or stance regarding the concept or experience of love.
-
E.
moreExpressiveThan
Indicates that one entity conveys ideas, emotions, or information with greater richness, nuance, or clarity than another.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa27f048190bed33a98e28c8d09 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:44 p.m.