Triple
T26989088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Choupette |
E679816
|
entity |
| Predicate | hasOwnPersonalDoctor |
P40116
|
FINISHED |
| Object | veterinarian |
—
|
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: veterinarian | Statement: [Choupette, hasOwnPersonalDoctor, veterinarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOwnPersonalDoctor Context triple: [Choupette, hasOwnPersonalDoctor, veterinarian]
-
A.
hasDoctorActor
Indicates that a doctor participates as an acting agent in the specified event or relationship.
-
B.
hasDoctorCharacter
Indicates that an entity includes or features a character whose role or profession is that of a doctor.
-
C.
hasHealthcareProvider
chosen
Indicates that one entity receives healthcare services or medical oversight from another entity acting as its healthcare provider.
-
D.
hasOwnHealthSystem
Indicates that an entity operates and controls its own dedicated healthcare system, rather than relying solely on external or shared health services.
-
E.
hasMedicalAttendant
Indicates that one entity serves as a medical attendant (e.g., providing medical care or supervision) for another entity.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 6:50 a.m.