Triple
T30878143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian Gnessin Academy of Music faculty |
E786534
|
entity |
| Predicate | alsoTeachesIn |
P170596
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Russian Gnessin Academy of Music faculty, alsoTeachesIn, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoTeachesIn Context triple: [Russian Gnessin Academy of Music faculty, alsoTeachesIn, English]
-
A.
areTaughtIn
Indicates that certain subjects, courses, or topics are instructed or delivered within specific locations, classes, or educational settings.
-
B.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
-
C.
isTaughtAs
Indicates that something is presented or delivered as instructional content, typically within an educational or training context.
-
D.
containsTeachingOf
Indicates that one entity includes, embodies, or presents the teaching, doctrine, or instructional content associated with another entity.
-
E.
hasTeaching
Indicates that one entity provides instruction or educational guidance to 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_69f224bae17c8190bb3a6a28e3d019df |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f691d87f788190bee65deb3a59057f |
completed | May 3, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68fb914b88190b0cad83ea9fe9dfc |
completed | May 2, 2026, 11:58 p.m. |
Created at: April 29, 2026, 8:48 p.m.