Triple
T13564332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Murchison |
E323993
|
entity |
| Predicate | viewsBeneathasAfricanInterestsAs |
P43390
|
FINISHED |
| Object | pretentious |
—
|
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: pretentious | Statement: [George Murchison, viewsBeneathasAfricanInterestsAs, pretentious]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewsBeneathasAfricanInterestsAs Context triple: [George Murchison, viewsBeneathasAfricanInterestsAs, pretentious]
-
A.
culturalInterest
Indicates a relationship where one entity has an interest in, appreciation for, or engagement with the culture, traditions, or cultural expressions associated with another entity.
-
B.
motionRelativeToAfrica
Indicates the movement or change in position of something as measured or defined relative to the African continent.
-
C.
viewOnInterest
chosen
Indicates a perspective, opinion, or stance that one entity holds regarding a particular interest or topic.
-
D.
usesPanAfricanColors
Indicates that one entity employs or incorporates the Pan-African colors (typically red, black, green, and sometimes yellow) in relation to another entity.
-
E.
subjectInterest
Indicates that the subject has an interest in, or is concerned with, the object.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00bbe848190bb33efe2af528295 |
completed | April 12, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.