Triple
T14981635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Kaufmann |
E373588
|
entity |
| Predicate | hasGivenInvitedTalkOn |
P10206
|
FINISHED |
| Object | automated reasoning with ACL2 |
—
|
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: automated reasoning with ACL2 | Statement: [Matt Kaufmann, hasGivenInvitedTalkOn, automated reasoning with ACL2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGivenInvitedTalkOn Context triple: [Matt Kaufmann, hasGivenInvitedTalkOn, automated reasoning with ACL2]
-
A.
succeededAsSpeakerBy
Indicates that one entity took over the role or position of speaker from another entity as their successor.
-
B.
hadConference
Indicates that a conference event took place involving the specified entities (such as participants, organizations, or locations).
-
C.
spokeAt
chosen
Indicates that a person delivered a talk, speech, or presentation at a particular event or location.
-
D.
gaveLecturesAt
Indicates that a person delivered lectures or taught courses at a particular institution or location.
-
E.
officeHeldAsSpeakerEnd
Indicates the point in time or date when an individual's tenure in the role of Speaker of a body or assembly comes to an end.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6fe42a081909308f788fdf024d5 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:52 a.m.