Triple
T19833244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wayne as Wil Andersen |
E476514
|
entity |
| Predicate | mentorsYoungCowboys |
P137503
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [John Wayne as Wil Andersen, mentorsYoungCowboys, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentorsYoungCowboys Context triple: [John Wayne as Wil Andersen, mentorsYoungCowboys, yes]
-
A.
coachesWith
Indicates that one entity serves as a coach or trainer in relation to another entity.
-
B.
youthLeader
Indicates that an entity holds a leadership role within a youth-focused group, organization, or activity.
-
C.
coachesInclude
Indicates that a set, group, or collection of coaches contains or includes a particular coach or subset of coaches.
-
D.
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.
-
E.
beganUnderCoach
Indicates that one entity started its activity, career, or involvement while being coached or supervised by another entity.
- F. None of above. chosen
Provenance (4 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656cf7e488190b4be28b5e7b363bf |
completed | April 20, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:50 p.m.