Triple
T12143703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Clermont-Ferrand |
E289259
|
entity |
| Predicate | employedAsPosition |
P47952
|
FINISHED |
| Object | Michel Foucault – academic staff member |
—
|
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: Michel Foucault – academic staff member | Statement: [University of Clermont-Ferrand, employedAsPosition, Michel Foucault – academic staff member]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employedAsPosition Context triple: [University of Clermont-Ferrand, employedAsPosition, Michel Foucault – academic staff member]
-
A.
employedTo
Indicates that one entity is hired or engaged to perform work, services, or duties for another entity.
-
B.
employedRole
Indicates that an entity holds or performs a specific role or position within an employment or work context.
-
C.
workPosition
chosen
Indicates the specific job role or position that an entity holds within an organization or workplace.
-
D.
employedThrough
Indicates that an entity holds a job or work position by means of, or via the arrangement of, another entity (such as an agency, contractor, or intermediary).
-
E.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.