Triple
T878862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grob G 120 |
E18980
|
entity |
| Predicate | typicalInstructorPosition |
P21025
|
FINISHED |
| Object | right seat |
—
|
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: right seat | Statement: [Grob G 120, typicalInstructorPosition, right seat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalInstructorPosition Context triple: [Grob G 120, typicalInstructorPosition, right seat]
-
A.
hasTeachingRole
Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
-
B.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
-
C.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
D.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
E.
typicalCourse
Indicates that one entity is a standard or commonly taken course associated with another entity, such as a program, curriculum, or field of study.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acb1dc20819095b9bb093158b60d |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8d47c081909b02a53e305ccf7a |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab9634948190b25ea1b2e34df87d |
completed | March 1, 2026, 9:11 p.m. |
Created at: March 1, 2026, 7:39 p.m.