Triple
T29188696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Padawan |
E739936
|
entity |
| Predicate | mentoredThrough |
P32710
|
FINISHED |
| Object | master–apprentice relationship |
—
|
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: master–apprentice relationship | Statement: [Padawan, mentoredThrough, master–apprentice relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentoredThrough Context triple: [Padawan, mentoredThrough, master–apprentice relationship]
-
A.
mentorOrPartner
chosen
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.
taughtThrough
Indicates that one entity provided instruction, education, or training to another entity by means of a specified method, medium, or intermediary.
-
C.
mentorOrAppointer
Indicates a relationship where one entity either serves as a mentor to another or is responsible for appointing that entity to a role or position.
-
D.
guidedBy
Indicates that an entity’s actions, decisions, or movement are directed, advised, or led by another entity.
-
E.
masteredBy
Indicates that a subject (such as a skill, topic, or resource) has been fully learned, controlled, or become highly proficiently used by a particular agent or 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f66388afe48190a68caf56c9745007 |
completed | May 2, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 12:01 p.m.