Triple
T29203750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debbie Joffe Ellis |
E740351
|
entity |
| Predicate | givesLectureOn |
P21344
|
FINISHED |
| Object | Rational Emotive Behavior Therapy |
—
|
NE NERFINISHED |
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: Rational Emotive Behavior Therapy | Statement: [Debbie Joffe Ellis, givesLectureOn, Rational Emotive Behavior Therapy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: givesLectureOn Context triple: [Debbie Joffe Ellis, givesLectureOn, Rational Emotive Behavior Therapy]
-
A.
gaveLecturesAt
Indicates that a person delivered lectures or taught courses at a particular institution or location.
-
B.
lecturesHeldIn
Indicates that a lecture event takes place or is conducted within a specific location or venue.
-
C.
teachesAbout
chosen
Indicates that one entity provides instruction or information to another entity on a particular subject or topic.
-
D.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
-
E.
notableLecturer
Indicates that a person is recognized as a distinguished or prominent lecturer, often due to their expertise, impact, or reputation in giving lectures.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f663c7b4f48190b66f966af570e768 |
completed | May 2, 2026, 8:51 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 12:08 p.m.