Triple
T20325437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luba |
E492319
|
entity |
| Predicate | artInfluenceOn |
P20089
|
FINISHED |
| Object | Central African art history |
—
|
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: Central African art history | Statement: [Luba, artInfluenceOn, Central African art history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artInfluenceOn Context triple: [Luba, artInfluenceOn, Central African art history]
-
A.
influenceOnArt
chosen
Indicates that one entity has affected, shaped, or inspired the artistic style, content, or development of another.
-
B.
designInfluenceOn
Indicates that one design, designer, or design-related factor has an effect on shaping, guiding, or altering another design or design outcome.
-
C.
movementInfluences
Indicates that one entity’s movement affects, alters, or determines the movement or motion-related behavior of another entity.
-
D.
wereInfluencedBy
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
E.
creativeInfluence
Indicates that one entity has shaped, inspired, or informed the creative work, style, or ideas of another 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6778f20288190b1862d6be61bfb67 |
completed | April 20, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69e5762655ac8190a8cc48a29fa2c0c4 |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:21 a.m.