Triple
T21089925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alex Azar |
E519608
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Alex Azar |
—
|
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: Alex Azar | Statement: [Alex Azar, name, Alex Azar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alex Azar Context triple: [Alex Azar, name, Alex Azar]
-
A.
Alex Azar
chosen
Alex Azar is an American attorney and pharmaceutical executive who served as the U.S. Secretary of Health and Human Services under President Donald Trump.
-
B.
Jonathan Mardukas
Jonathan Mardukas is a neurotic yet principled accountant-turned-informant on the run from both the mob and law enforcement in the action-comedy film "Midnight Run."
-
C.
Tom Price
Tom Price is a remote mining town in Western Australia’s Pilbara region, known primarily for its large iron ore operations and surrounding rugged outback landscapes.
-
D.
Tom Price
Tom Price is an American physician and Republican politician who served as the U.S. Secretary of Health and Human Services under President Donald Trump.
-
E.
Tom Price
Tom Price is a fictional character portrayed by actor Justin Chatwin, best known from the television series "American Gothic."
- 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7094dd65481909391ed74115afc23 |
completed | April 21, 2026, 5:21 a.m. |
Created at: April 16, 2026, 2:50 p.m.