Triple
T35327584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edgar Balthazar |
E1020230
|
entity |
| Predicate | petPeeve |
P179788
|
FINISHED |
| Object | Madame's 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: Madame's cats | Statement: [Edgar Balthazar, petPeeve, Madame's cats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: petPeeve Context triple: [Edgar Balthazar, petPeeve, Madame's cats]
-
A.
hasPetPeeve
chosen
Indicates that one entity has a particular annoyance or irritation (a pet peeve) directed toward or associated with another entity or situation.
-
B.
pet
Indicates that one entity keeps another animal for companionship or pleasure, typically providing care and shelter.
-
C.
companionAnimals
Indicates a relationship where one entity keeps or cares for another entity as a pet or companion animal.
-
D.
involvedAnimal
Indicates that an animal participates in, is affected by, or is otherwise directly connected to the event or situation described.
-
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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.