Triple
T26218716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renoir family |
E655705
|
entity |
| Predicate | hasArtisticLegacyIn |
P42607
|
FINISHED |
| Object | French cinema |
—
|
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: French cinema | Statement: [Renoir family, hasArtisticLegacyIn, French cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArtisticLegacyIn Context triple: [Renoir family, hasArtisticLegacyIn, French cinema]
-
A.
hasArtisticReputation
Indicates that an entity is recognized or regarded for its artistic skill, contribution, or standing.
-
B.
hasCulturalLegacyIn
chosen
Indicates that an entity has left a lasting cultural influence, impact, or heritage within a particular place, community, or cultural context.
-
C.
hasArtisticWorks
Indicates that an entity possesses, is associated with, or is the creator of one or more artistic works.
-
D.
hasFamousArtwork
Indicates that an entity possesses or is associated with a well-known or widely recognized artwork.
-
E.
hasArtisticOrigin
Indicates that something originates from, is derived from, or is rooted in an artistic source, style, or tradition.
- 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_69ee5b4a77e08190bfcb5f8ecdc55abd |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 26, 2026, 8:55 p.m.