Triple
T31092648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1912 Salon d'Automne |
E792430
|
entity |
| Predicate | hasWorkExhibited |
P193946
|
FINISHED |
| Object | La Femme au Cheval |
—
|
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: La Femme au Cheval | Statement: [1912 Salon d'Automne, hasWorkExhibited, La Femme au Cheval]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkExhibited Context triple: [1912 Salon d'Automne, hasWorkExhibited, La Femme au Cheval]
-
A.
hasTypeOfWorkExhibited
Indicates that a subject (such as an exhibition or venue) features or displays a particular type or category of work.
-
B.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
C.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
-
D.
hasNotableWorkSetThere
Indicates that a notable work (such as a book, film, or other creative piece) is set in or takes place within the referenced location.
-
E.
hasPeriodOfWorks
Indicates that an entity’s works are associated with, or belong to, a specific time period or phase.
- 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_69f224cf157c81909e2d2bd88c9282c3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd5bf69acc819092a01e4259785dc3 |
completed | May 8, 2026, 3:43 a.m. |
| PD | Predicate disambiguation | batch_69fd59b3f4ac8190a7f9dd3142da6e09 |
completed | May 8, 2026, 3:34 a.m. |
| PDg | Predicate description generation | batch_69fd5bf49288819098a12202411cba4f |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 29, 2026, 9:02 p.m.