Triple
T31233856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Landon |
E796359
|
entity |
| Predicate | hasProfessionAfterActing |
P128960
|
FINISHED |
| Object | clinical psychologist |
—
|
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: clinical psychologist | Statement: [Leslie Landon, hasProfessionAfterActing, clinical psychologist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionAfterActing Context triple: [Leslie Landon, hasProfessionAfterActing, clinical psychologist]
-
A.
hasFilmCareer
Indicates that an entity has been professionally involved in the film industry as a career.
-
B.
postActingOccupation
chosen
Indicates the occupation or role a person holds after their acting career has ended.
-
C.
hasProfessionalCareer
Indicates that an entity engages in or has engaged in a recognized professional occupation or career over a period of time.
-
D.
starsLaterCareerRoleOf
Indicates that one entity plays a starring role in a later phase or version of another entity’s career or role.
-
E.
hasGivenProfession
Indicates that an entity holds or practices a specified profession or occupation.
- 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_69f224db69ac81909a370adad6a7ac7c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00512437d48190ad20324968ead5f4 |
completed | May 10, 2026, 9:34 a.m. |
| PD | Predicate disambiguation | batch_6a0050227350819099f41369c3d168be |
completed | May 10, 2026, 9:30 a.m. |
Created at: April 29, 2026, 9:10 p.m.