Triple
T11988943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucille |
E285353
|
entity |
| Predicate | hasInfluenceOnArtistCommunity |
P13951
|
FINISHED |
| Object | later rock musicians |
—
|
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: later rock musicians | Statement: [Lucille, hasInfluenceOnArtistCommunity, later rock musicians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfluenceOnArtistCommunity Context triple: [Lucille, hasInfluenceOnArtistCommunity, later rock musicians]
-
A.
influencedArtist
chosen
Indicates that one artist has had a significant impact on the style, work, or development of another artist.
-
B.
influencesCommunity
Indicates that one entity has an effect on the behavior, attitudes, or conditions of a community.
-
C.
influenceOnArt
Indicates that one entity has affected, shaped, or inspired the artistic style, content, or development of another.
-
D.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
E.
hasPopularityInfluencedBy
Indicates that the popularity level of one entity is affected or shaped by another specified factor or entity.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903ae28708190a826bad1624343eb |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.