Triple
T16077019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Nunn |
E390003
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sam Nunn |
E390003
|
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: Sam Nunn | Statement: [Sam Nunn, name, Sam Nunn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sam Nunn Context triple: [Sam Nunn, name, Sam Nunn]
-
A.
Sam Nunn
chosen
Sam Nunn is a former United States Senator from Georgia known for his influential work on national security, defense policy, and nuclear nonproliferation.
-
B.
Don Payne
Don Payne was an American screenwriter and producer best known for his work on comedic television series like "The Simpsons" and superhero films such as "Thor."
-
C.
Jacob Raines
Jacob Raines is a fictional character from the television drama series "Good Behavior," which follows a con artist and thief trying to rebuild her life.
-
D.
Ernest Hollings
Ernest Hollings was a long-serving U.S. senator from South Carolina known for his influential role in federal budget policy and fiscal reform.
-
E.
Herb Conaway
Herb Conaway is an American physician and Democratic politician who has long served in the New Jersey General Assembly.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183c34508819084a53d13e55cbf69 |
completed | April 17, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe48907148190ab04520717141788 |
completed | May 10, 2026, 1:51 a.m. |
Created at: April 10, 2026, 4:57 a.m.