Triple
T19351500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Brackish Okun |
E484029
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Okun |
—
|
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: Okun | Statement: [Dr. Brackish Okun, hasSurname, Okun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Okun Context triple: [Dr. Brackish Okun, hasSurname, Okun]
-
A.
Okun
chosen
Okun is a surname most notably associated with figures such as economist Arthur Okun, known for Okun's law relating unemployment and economic output.
-
B.
Barro
Barro is a neighborhood located in the city of Recife, in the state of Pernambuco, Brazil.
-
C.
Easterlin
Easterlin is the surname of Richard A. Easterlin, an American economist known for formulating the Easterlin Paradox about the relationship between income and happiness.
-
D.
Engle
Engle is a surname most notably associated with Joe Engle, an American astronaut and test pilot.
-
E.
Rybczyński
Rybczyński is a Polish surname most notably associated with Oscar-winning experimental filmmaker and visual effects pioneer Zbigniew Rybczyński.
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e61904a878819084d58ed3b7d8a978 |
completed | April 20, 2026, 12:16 p.m. |
Created at: April 10, 2026, 1:34 p.m.