Triple
T27342703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dans l’ombre |
E684150
|
entity |
| Predicate | coAuthorOccupation |
P162199
|
FINISHED |
| Object | Prime Minister of France |
—
|
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: Prime Minister of France | Statement: [Dans l’ombre, coAuthorOccupation, Prime Minister of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coAuthorOccupation Context triple: [Dans l’ombre, coAuthorOccupation, Prime Minister of France]
-
A.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
-
B.
coAuthorshipType
Indicates the specific nature or category of the collaborative authorship relationship between two or more contributors.
-
C.
hasAuthorOccupationOfAuthor
Indicates that an author has a specific occupation or professional role.
-
D.
creatorOccupation
Indicates the professional role or job that the creator of an entity holds or held.
-
E.
coAuthorField
Indicates that two or more entities have jointly authored a work within the same academic or professional field.
- F. None of above. chosen
Provenance (4 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_69ef1480a76481908684256ddd5bfda3 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f62b9f5514819088c3a1e11c65a9af |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f620e4b1c88190a17940251abc68fd |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621fbfc2c8190bfa802d7dc0f6aa4 |
completed | May 2, 2026, 4:10 p.m. |
Created at: April 27, 2026, 11:43 a.m.