Triple
T28001956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Introductory Lectures on Psycho-Analysis |
E707169
|
entity |
| Predicate | settingOfLectures |
P16025
|
FINISHED |
| Object | University of Vienna |
—
|
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: University of Vienna | Statement: [Introductory Lectures on Psycho-Analysis, settingOfLectures, University of Vienna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfLectures Context triple: [Introductory Lectures on Psycho-Analysis, settingOfLectures, University of Vienna]
-
A.
courseSetting
chosen
Indicates the context or environment in which a course is delivered or conducted.
-
B.
numberOfLectures
Indicates the total count of lectures associated with a given entity or context.
-
C.
lectureSeries
Indicates a relationship where a set of lectures is organized and presented as a coherent, thematically linked series.
-
D.
includesLecture
Indicates that one entity (such as a course, module, or event) contains or is composed of a specific lecture as part of its structure or content.
-
E.
recitationSetting
Indicates the context or environment in which a recitation takes place, such as the type, location, or format of the recitation event.
- 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_69ef96b980d88190a753b2f9a978595a |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 27, 2026, 7:57 p.m.