Triple
T11319964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TV Writing Program |
E268066
|
entity |
| Predicate | mentorshipFrom |
P72506
|
FINISHED |
| Object | industry professionals |
—
|
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: industry professionals | Statement: [TV Writing Program, mentorshipFrom, industry professionals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentorshipFrom Context triple: [TV Writing Program, mentorshipFrom, industry professionals]
-
A.
mentorOrPartner
Indicates a relationship in which one entity either provides guidance and support to another as a mentor or collaborates with them on relatively equal footing as a partner.
-
B.
teachableFrom
Indicates that one entity can be taught or learned from another entity, capturing a directional teachability or learnability relationship between them.
-
C.
coachedFrom
chosen
Indicates that one entity served as a coach or trainer for another entity during a specified period or context.
-
D.
advisorOf
Indicates that one entity serves as an advisor, providing guidance or counsel, to another entity.
-
E.
teacherOrInfluence
Indicates that one entity serves as a teacher to, or has a significant influence on the development, behavior, or thinking of, 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9de875481908acfa56015d4b46f |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787ad575081908274280bf75d95fd |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.