Triple
T16213283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monday Morning Podcast |
E393518
|
entity |
| Predicate | hasCompanionContent |
P122192
|
FINISHED |
| Object | video clips on YouTube |
—
|
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: video clips on YouTube | Statement: [Monday Morning Podcast, hasCompanionContent, video clips on YouTube]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCompanionContent Context triple: [Monday Morning Podcast, hasCompanionContent, video clips on YouTube]
-
A.
includesCompanion
Indicates that one entity involves, contains, or is accompanied by another entity acting as a companion.
-
B.
hasCompanionPillar
Indicates that an entity is associated with or supported by a corresponding companion pillar.
-
C.
hasCompanionDocument
Indicates that one document is associated with and serves as a companion to another document.
-
D.
hasCompanionEvent
Indicates that one event is associated with another event that occurs alongside it as a related or accompanying occurrence.
-
E.
hasCompanionCandidate
Indicates that an entity is associated with another entity that is being considered or proposed as a potential companion.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e227f2c1288190bfaed49c364bfa22 |
completed | April 17, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:03 a.m.