Triple
T12407095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant Governor of Iowa |
E296416
|
entity |
| Predicate | officeHolder |
P537
|
FINISHED |
| Object |
Adam Gregg
Adam Gregg is an American politician and attorney who serves as the lieutenant governor of Iowa.
|
E989970
|
NE FINISHED |
How this triple was built (4 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: Adam Gregg | Statement: [Lieutenant Governor of Iowa, officeHolder, Adam Gregg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adam Gregg Context triple: [Lieutenant Governor of Iowa, officeHolder, Adam Gregg]
-
A.
Eric Gregg
Eric Gregg was a prominent Major League Baseball umpire known for his long tenure in the National League and his participation in several high-profile postseason games.
-
B.
Matthew Aldrich
Matthew Aldrich is an American screenwriter best known for co-writing Pixar’s Academy Award–winning animated film "Coco."
-
C.
Andrew Pyle
Andrew Pyle is a British philosopher known for his work in the philosophy of science, metaphysics, and the history of early modern philosophy.
-
D.
Adam Gough
Adam Gough is a British film editor known for his work on acclaimed films such as "Da 5 Bloods" and "Roma."
-
E.
Gregory Hess
Gregory Hess was an American protester whose conviction for disorderly conduct during an antiwar demonstration led to the landmark U.S. Supreme Court free speech case Hess v. Indiana.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Adam Gregg Triple: [Lieutenant Governor of Iowa, officeHolder, Adam Gregg]
Generated description
Adam Gregg is an American politician and attorney who serves as the lieutenant governor of Iowa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Adam Gregg Target entity description: Adam Gregg is an American politician and attorney who serves as the lieutenant governor of Iowa.
-
A.
Eric Gregg
Eric Gregg was a prominent Major League Baseball umpire known for his long tenure in the National League and his participation in several high-profile postseason games.
-
B.
Matthew Aldrich
Matthew Aldrich is an American screenwriter best known for co-writing Pixar’s Academy Award–winning animated film "Coco."
-
C.
Andrew Pyle
Andrew Pyle is a British philosopher known for his work in the philosophy of science, metaphysics, and the history of early modern philosophy.
-
D.
Adam Gough
Adam Gough is a British film editor known for his work on acclaimed films such as "Da 5 Bloods" and "Roma."
-
E.
Gregory Hess
Gregory Hess was an American protester whose conviction for disorderly conduct during an antiwar demonstration led to the landmark U.S. Supreme Court free speech case Hess v. Indiana.
- F. None of above. chosen
Provenance (5 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d4a08e0819085c656e35038e6b2 |
completed | April 10, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6556495208190abd2e3e5aaac57a5 |
completed | May 2, 2026, 7:49 p.m. |
| NEDg | Description generation | batch_69f6566dccc0819085e059c7b0288f6c |
completed | May 2, 2026, 7:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f65799ca588190b9f7a07f5c1a842c |
completed | May 2, 2026, 7:59 p.m. |
Created at: April 8, 2026, 9:55 p.m.