Triple
T36151767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pankaj K. Agarwal |
E1045603
|
entity |
| Predicate | hasGivenNamedLecture |
P184763
|
FINISHED |
| Object | Invited speaker at major computational geometry conferences |
—
|
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: Invited speaker at major computational geometry conferences | Statement: [Pankaj K. Agarwal, hasGivenNamedLecture, Invited speaker at major computational geometry conferences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGivenNamedLecture Context triple: [Pankaj K. Agarwal, hasGivenNamedLecture, Invited speaker at major computational geometry conferences]
-
A.
hasGivenLecturesOn
Indicates that one entity has delivered or presented lectures on a particular subject, topic, or field to an audience.
-
B.
lecturedOn
Indicates that one entity delivered a lecture or formal talk about a particular subject or topic to an audience.
-
C.
hasLecturer
Indicates that an educational course, class, or module is taught or overseen by a specific lecturer.
-
D.
lecturesHeldIn
Indicates that a lecture event takes place or is conducted within a specific location or venue.
-
E.
gaveLecturesAt
Indicates that a person delivered lectures or taught courses at a particular institution or location.
- 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_69f76e38903c8190a52887620f90aabe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b3e0f1c88190985feab6cee8b05e |
completed | May 3, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:08 p.m.