Triple
T1841349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Rose Window of Notre-Dame de Paris |
E41182
|
entity |
| Predicate | hasArtTechnique |
P14965
|
FINISHED |
| Object | medieval stained-glass painting |
—
|
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: medieval stained-glass painting | Statement: [North Rose Window of Notre-Dame de Paris, hasArtTechnique, medieval stained-glass painting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArtTechnique Context triple: [North Rose Window of Notre-Dame de Paris, hasArtTechnique, medieval stained-glass painting]
-
A.
artisticTechnique
chosen
Indicates the method, style, or process used to create or execute an artistic work.
-
B.
hasTechnique
Indicates that an entity employs, utilizes, or is associated with a particular method, procedure, or technique.
-
C.
hasArtisticDiscipline
Indicates that one entity practices, specializes in, or is associated with a particular artistic discipline or field.
-
D.
hasArtisticGenre
Indicates that an entity (such as a work or creation) belongs to or is characterized by a particular artistic genre.
-
E.
hasArtProgram
Indicates that an entity offers or participates in an art-related educational or creative program.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdb0d2c8190a67f584e67979fa3 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.