Triple
T7169836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Schweiker |
E167164
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Schweiker |
E167164
|
NE 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: Schweiker | Statement: [Mark Schweiker, familyName, Schweiker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schweiker Context triple: [Mark Schweiker, familyName, Schweiker]
-
A.
Mark Schweiker
chosen
Mark Schweiker is an American politician who served as the 44th governor of Pennsylvania in the early 2000s.
-
B.
Mick Mulvaney
Mick Mulvaney is an American politician and former U.S. Representative who served in the Trump administration in senior roles, including as acting White House Chief of Staff and Director of the Office of Management and Budget.
-
C.
Chad Wolf
Chad Wolf is an American government official who served as acting Secretary of Homeland Security under President Donald Trump.
-
D.
Ryan Zinke
Ryan Zinke is an American politician and former U.S. Navy SEAL who served as the United States Secretary of the Interior under President Donald Trump.
-
E.
Kim Reynolds
Kim Reynolds is an American Republican politician serving as the governor of Iowa and known for her conservative policies on taxes, education, and public health.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e85d8f208190915f6f4c05988b63 |
completed | March 27, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b910c2688190b28573c5d58542d5 |
completed | March 28, 2026, 11:18 a.m. |
Created at: March 27, 2026, 2:48 p.m.