Triple
T28374814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Animation Academy |
E718727
|
entity |
| Predicate | teachesCharactersFrom |
P167351
|
FINISHED |
| Object | Disney animated films |
—
|
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: Disney animated films | Statement: [Animation Academy, teachesCharactersFrom, Disney animated films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachesCharactersFrom Context triple: [Animation Academy, teachesCharactersFrom, Disney animated films]
-
A.
teachableFrom
Indicates that one entity can be taught or learned from another entity, capturing a directional teachability or learnability relationship between them.
-
B.
didacticCharacter
Indicates that one entity serves a teaching or instructional role toward another, conveying guidance, lessons, or moral instruction.
-
C.
teachesPo
Indicates that one entity provides instruction or education to another entity.
-
D.
teachesAbout
Indicates that one entity provides instruction or information to another entity on a particular subject or topic.
-
E.
learnsLanguageFrom
Indicates that one entity acquires or improves knowledge of a language through instruction, exposure, or guidance provided 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f66a6468ec8190a43ed6cd8c797f42 |
completed | May 2, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f6659b62fc8190b21555d0ba54db2d |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 28, 2026, 1:02 a.m.