Triple
T34368601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Third Secret |
E882087
|
entity |
| Predicate | psychiatristCharacter |
P127445
|
FINISHED |
| Object | Dr. Leo Whitset |
—
|
NE NERFINISHED |
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: Dr. Leo Whitset | Statement: [The Third Secret, psychiatristCharacter, Dr. Leo Whitset]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: psychiatristCharacter Context triple: [The Third Secret, psychiatristCharacter, Dr. Leo Whitset]
-
A.
therapist
Indicates that one entity serves in a therapeutic role, providing professional mental health or counseling services to another entity.
-
B.
hasDoctorCharacter
chosen
Indicates that an entity includes or features a character whose role or profession is that of a doctor.
-
C.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
D.
mentorCharacter
Indicates that one character serves as a mentor, providing guidance, teaching, or support to another character.
-
E.
patientPortrayedBy
Indicates that a patient is represented or depicted by a particular actor, model, or illustrative figure.
- 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_69f349be5c9c81908dc726ae1f4c68f2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:58 a.m.