Triple
T35477506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Adelaide Bonfamille |
E1025375
|
entity |
| Predicate | affectionFor |
P140057
|
FINISHED |
| Object | cats |
—
|
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: cats | Statement: [Madame Adelaide Bonfamille, affectionFor, cats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectionFor Context triple: [Madame Adelaide Bonfamille, affectionFor, cats]
-
A.
affectionReciprocated
Indicates that feelings of affection expressed by one entity toward another are mutually returned by the other entity.
-
B.
objectOfAffectionFor
chosen
Indicates that one entity is the target or recipient of another entity’s romantic or affectionate feelings.
-
C.
competesForAffectionWith
Indicates a relationship where two or more entities vie against each other to gain the affection or emotional favor of the same target entity.
-
D.
hasAffectionateUse
Indicates that one entity uses or refers to another in a loving, tender, or emotionally warm manner.
-
E.
animalTypeLoved
Indicates that one entity loves or is especially fond of animals of a particular type.
- 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_69f76dfadba0819083456aadcd6864ea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:04 p.m.