Triple
T7703289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Two Americas |
E174551
|
entity |
| Predicate | usedToCriticize |
P50924
|
FINISHED |
| Object | economic policies favoring the wealthy |
—
|
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: economic policies favoring the wealthy | Statement: [Two Americas, usedToCriticize, economic policies favoring the wealthy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToCriticize Context triple: [Two Americas, usedToCriticize, economic policies favoring the wealthy]
-
A.
usedToCritique
chosen
Indicates that something is employed as a means to analyze, evaluate, or express disapproval of something else.
-
B.
criticizedFor
Indicates that one entity expresses disapproval or negative judgment of another entity specifically because of a particular action, quality, or outcome.
-
C.
hasCriticism
Indicates that one entity expresses disapproval, objection, or negative evaluation directed toward another entity.
-
D.
aimsToCritique
Indicates an intention to analyze and point out faults, limitations, or weaknesses in something.
-
E.
criticizedConstruct
Indicates that one entity expressed disapproval or negative judgment about another entity’s constructed work, idea, or creation.
- 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_69c6995a72cc8190998e56daa6f8e453 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70402169481909b219dc5f4a64b9b |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c70165e78c8190bf6b3c34e243cb81 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:03 p.m.