Triple
T160663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vincent van Gogh |
E3276
|
entity |
| Predicate | numberOfPaintingsCreated |
P6224
|
FINISHED |
| Object | over 800 oil paintings |
—
|
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: over 800 oil paintings | Statement: [Vincent van Gogh, numberOfPaintingsCreated, over 800 oil paintings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPaintingsCreated Context triple: [Vincent van Gogh, numberOfPaintingsCreated, over 800 oil paintings]
-
A.
paintedEvery
Indicates that an entity applied paint to each and every relevant item in a specified set or domain.
-
B.
hasPublicArtwork
Indicates that a location or entity possesses or features artwork that is accessible to the general public.
-
C.
hasArtInstallation
Indicates that an entity features or contains an art installation as part of its space or composition.
-
D.
hasArtProgram
Indicates that an entity offers or participates in an art-related educational or creative program.
-
E.
articleCount
Indicates the number of articles associated with a given entity or context.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a25856d934819095460b2ea566eb6b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256623704819089d9eeefe05858ce |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2578329d08190be82e004b8224d2b |
completed | Feb. 28, 2026, 2:48 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.