Triple
T8099915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Gogh's final works |
E189081
|
entity |
| Predicate | approximateNumberOfPaintings |
P5764
|
FINISHED |
| Object | 70 |
—
|
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: 70 | Statement: [Van Gogh's final works, approximateNumberOfPaintings, 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfPaintings Context triple: [Van Gogh's final works, approximateNumberOfPaintings, 70]
-
A.
estimatedNumberOfPaintings
chosen
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
-
B.
numberOfPaintingsCreated
Indicates the total count of paintings that an entity has created.
-
C.
numberOfPaintedSculptures
Indicates the quantity of sculptures that have been painted in a given context or collection.
-
D.
articleCountApprox
Indicates that the relationship specifies an approximate number of articles associated with an entity.
-
E.
numberOfSculptures
Indicates the quantity of sculptures associated with a given entity or context.
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42ba9af88190b6310d799818e3d5 |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:31 p.m.