Triple
T23165204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place André-Malraux |
E578693
|
entity |
| Predicate | eponymNotableOffice |
P125468
|
FINISHED |
| Object | French Minister of Cultural Affairs |
—
|
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: French Minister of Cultural Affairs | Statement: [Place André-Malraux, eponymNotableOffice, French Minister of Cultural Affairs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eponymNotableOffice Context triple: [Place André-Malraux, eponymNotableOffice, French Minister of Cultural Affairs]
-
A.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
-
B.
eponymKnownFor
Indicates that a person or entity is widely recognized or named as the source or inspiration for something else (such as a concept, place, or object).
-
C.
eponymHeldPosition
chosen
Indicates that the person after whom something is named once held a particular position or role.
-
D.
eponymFoundedOrganization
Indicates that a person, whose name is used as the eponym, founded the specified organization.
-
E.
eponymPlayedFor
Indicates that the eponymous person or entity was a member of, or played for, a particular team or organization.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f2bca4881909f6148d588948018 |
completed | April 29, 2026, 4:55 a.m. |
| PD | Predicate disambiguation | batch_69ef89ff76808190808ee4ad9dea776b |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:03 p.m.