Triple
T25610695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foucault’s Collège de France lecture publications |
E642040
|
entity |
| Predicate | locationOfLectures |
P44244
|
FINISHED |
| Object | Collège de France |
—
|
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: Collège de France | Statement: [Foucault’s Collège de France lecture publications, locationOfLectures, Collège de France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfLectures Context triple: [Foucault’s Collège de France lecture publications, locationOfLectures, Collège de France]
-
A.
lecturesHeldIn
chosen
Indicates that a lecture event takes place or is conducted within a specific location or venue.
-
B.
homeCourseLocation
Indicates the location where an entity’s primary or home course is situated.
-
C.
numberOfLectures
Indicates the total count of lectures associated with a given entity or context.
-
D.
gaveLecturesAt
Indicates that a person delivered lectures or taught courses at a particular institution or location.
-
E.
lecturedOn
Indicates that one entity delivered a lecture or formal talk about a particular subject or topic to an audience.
- 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_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f791cc969c8190bf187d6031a030d5 |
completed | May 3, 2026, 6:19 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
Created at: April 21, 2026, 4:41 p.m.