Triple
T12984572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercator projection |
E321733
|
entity |
| Predicate | commonlyCriticizedFor |
P53756
|
FINISHED |
| Object | Eurocentric visual bias |
—
|
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: Eurocentric visual bias | Statement: [Mercator projection, commonlyCriticizedFor, Eurocentric visual bias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyCriticizedFor Context triple: [Mercator projection, commonlyCriticizedFor, Eurocentric visual bias]
-
A.
criticizedFor
Indicates that one entity expresses disapproval or negative judgment of another entity specifically because of a particular action, quality, or outcome.
-
B.
sometimesCriticizedFor
chosen
Indicates that an entity is on occasion the target of criticism for a particular reason, behavior, or attribute.
-
C.
hasCriticism
Indicates that one entity expresses disapproval, objection, or negative evaluation directed toward another entity.
-
D.
criticizedConstruct
Indicates that one entity expressed disapproval or negative judgment about another entity’s constructed work, idea, or creation.
-
E.
criticismReason
Indicates that one entity criticizes another entity specifically because of the stated reason.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:40 p.m.