Triple
T14341852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin C. Pierce |
E355622
|
entity |
| Predicate | hasTaughtCourseOn |
P34091
|
FINISHED |
| Object | types and programming languages |
—
|
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: types and programming languages | Statement: [Benjamin C. Pierce, hasTaughtCourseOn, types and programming languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTaughtCourseOn Context triple: [Benjamin C. Pierce, hasTaughtCourseOn, types and programming languages]
-
A.
taughtCourse
chosen
Indicates that an entity (typically an instructor) has taught a particular course.
-
B.
hasTeaching
Indicates that one entity provides instruction or educational guidance to another entity.
-
C.
areTaughtIn
Indicates that certain subjects, courses, or topics are instructed or delivered within specific locations, classes, or educational settings.
-
D.
gaveLecturesAt
Indicates that a person delivered lectures or taught courses at a particular institution or location.
-
E.
hasTeachingActivity
Indicates that an entity engages in or is associated with a specific teaching-related activity or instructional role.
- F. None of above.
Provenance (3 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e87febc8190a63c668cbd0fd713 |
completed | April 14, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69de2a9958e881909d03ac03f135163e |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:14 a.m.