Triple
T3978397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1905 Salon d’Automne exhibition in Paris |
E85696
|
entity |
| Predicate | numberOfWorksByMatisse |
P6221
|
FINISHED |
| Object | approximately 10 |
—
|
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: approximately 10 | Statement: [1905 Salon d’Automne exhibition in Paris, numberOfWorksByMatisse, approximately 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWorksByMatisse Context triple: [1905 Salon d’Automne exhibition in Paris, numberOfWorksByMatisse, approximately 10]
-
A.
estimatedNumberOfPaintings
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
-
B.
numberOfWorks
chosen
Indicates the total count of works associated with a given entity.
-
C.
numberOfPaintingsCreated
Indicates the total count of paintings that an entity has created.
-
D.
numberOfWorksCreated
Indicates the total count of creative works that an entity has produced or authored.
-
E.
worksCollectedBy
Indicates that one entity gathers, compiles, or curates the works (such as creations, publications, or outputs) produced by another entity.
- 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_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa3ef7ac8190abe02f440ff83c43 |
completed | March 9, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69aef8f492ac819089dbb9436dbcdd2b |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.