Triple
T15240066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Cézanne in a Blue Dress |
E364230
|
entity |
| Predicate | hasPortrayalQuality |
P117701
|
FINISHED |
| Object | reserved mood |
—
|
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: reserved mood | Statement: [Madame Cézanne in a Blue Dress, hasPortrayalQuality, reserved mood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortrayalQuality Context triple: [Madame Cézanne in a Blue Dress, hasPortrayalQuality, reserved mood]
-
A.
portrayalRecognition
Indicates that one entity recognizes or identifies another entity as a portrayal or representation of a particular subject or character.
-
B.
hasPortrait
Indicates that one entity possesses, displays, or is associated with a portrait depicting another entity.
-
C.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
D.
portrayalReceived
Indicates that an entity has been depicted or represented by another entity, such as through an image, performance, or description.
-
E.
portrayalFormat
Indicates the medium or format in which something is portrayed or represented (e.g., painting, sculpture, film, digital).
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007db9a148190aadea8d5f8b6b261 |
completed | April 15, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2ca6148190967c319728ec3661 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:13 a.m.