Triple
T2461069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maand |
E54533
|
entity |
| Predicate | taughtThrough |
P40656
|
FINISHED |
| Object | oral tradition |
—
|
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: oral tradition | Statement: [Maand, taughtThrough, oral tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: taughtThrough Context triple: [Maand, taughtThrough, oral tradition]
-
A.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
-
B.
taughtCourse
Indicates that an entity (typically an instructor) has taught a particular course.
-
C.
isTaughtAs
Indicates that something is presented or delivered as instructional content, typically within an educational or training context.
-
D.
hasTeaching
Indicates that one entity provides instruction or educational guidance to another entity.
-
E.
coreTeaching
Indicates that an entity serves as a primary or foundational teaching or instructional activity for 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd49b5d2481908817aeb171e2bd61 |
completed | March 7, 2026, 7:32 a.m. |
Created at: March 6, 2026, 9:44 p.m.