Triple
T25438633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kshitij |
E637441
|
entity |
| Predicate | hasLectureSeries |
P45279
|
FINISHED |
| Object | talks by industry experts |
—
|
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: talks by industry experts | Statement: [Kshitij, hasLectureSeries, talks by industry experts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLectureSeries Context triple: [Kshitij, hasLectureSeries, talks by industry experts]
-
A.
lectureSeries
chosen
Indicates a relationship where a set of lectures is organized and presented as a coherent, thematically linked series.
-
B.
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.
-
C.
lecturesHeldIn
Indicates that a lecture event takes place or is conducted within a specific location or venue.
-
D.
hasLecturer
Indicates that an educational course, class, or module is taught or overseen by a specific lecturer.
-
E.
hasEventSeries
Indicates that an entity is associated with, or participates in, a sequence of related events forming a series.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 21, 2026, 2 p.m.