Triple
T9440680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timothy J. Power |
E227636
|
entity |
| Predicate | hasGivenAcademicTalkAt |
P36187
|
FINISHED |
| Object | various universities in the United Kingdom |
—
|
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: various universities in the United Kingdom | Statement: [Timothy J. Power, hasGivenAcademicTalkAt, various universities in the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGivenAcademicTalkAt Context triple: [Timothy J. Power, hasGivenAcademicTalkAt, various universities in the United Kingdom]
-
A.
gaveLecturesAt
chosen
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.
notableLecturer
Indicates that a person is recognized as a distinguished or prominent lecturer, often due to their expertise, impact, or reputation in giving lectures.
-
D.
yearLecturesDelivered
Indicates the specific year in which the lectures were delivered.
-
E.
conferenceSince
Indicates that a conference-related relationship or interaction between entities has been in effect continuously since a specified point in time.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee36f908190826994db91b18466 |
completed | April 1, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69cca55548488190b171ae695a3212de |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:50 p.m.