Triple
T15336861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Cézanne |
E366688
|
entity |
| Predicate | numberOfKnownPortraits |
P118166
|
FINISHED |
| Object | over 20 |
—
|
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 20 | Statement: [Madame Cézanne, numberOfKnownPortraits, over 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfKnownPortraits Context triple: [Madame Cézanne, numberOfKnownPortraits, over 20]
-
A.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
-
B.
depictsInPortraits
Indicates that one entity is represented or shown as the subject within portrait images created by another entity.
-
C.
estimatedNumberOfPaintings
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
-
D.
numberOfBlackPaintings
Indicates the count of paintings in the subject entity that are classified as black paintings.
-
E.
eraDepicted
Indicates that a work or representation portrays, illustrates, or is set in a particular historical era or time period.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e11b22c81908280efe65acd5454 |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:17 a.m.