Triple
T20351969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poor Economics |
E496034
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Esther Duflo |
—
|
NE NERFINISHED |
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: Esther Duflo | Statement: [Poor Economics, author, Esther Duflo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esther Duflo Context triple: [Poor Economics, author, Esther Duflo]
-
A.
Esther Duflo
chosen
Esther Duflo is a French-American economist and Nobel laureate renowned for her pioneering use of randomized controlled trials to study and combat global poverty.
-
B.
Abhijit Banerjee
Abhijit Banerjee is an Indian-American economist and Nobel laureate renowned for his experimental approach to alleviating global poverty.
-
C.
Susan Athey
Susan Athey is an influential American economist known for her pioneering work in applied microeconomics, market design, and the economics of technology and digital platforms.
-
D.
Michael Kremer
Michael Kremer is an American development economist and Nobel laureate known for pioneering the use of randomized controlled trials to evaluate anti-poverty programs.
-
E.
Davida McKenzie
Davida McKenzie is a New Zealand actress best known for her role in the 2021 horror film "Silent Night."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67850ace48190b19aff5780fef7e8 |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:24 a.m.