Triple
T18270478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nat Adderley Jr. |
E437594
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nat |
—
|
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: Nat | Statement: [Nat Adderley Jr., givenName, Nat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nat Context triple: [Nat Adderley Jr., givenName, Nat]
-
A.
Nat
Nat is a fictional character from Louisa May Alcott's novel "Jo's Boys," known as one of the former students of Plumfield whose adult life and growth are followed in the story.
-
B.
Nat
Nat is the given name of Nat Turner, the African-American preacher who led a major slave rebellion in Virginia in 1831.
-
C.
Nat
chosen
Nat is a masculine given name, often used as a shortened form of names like Nathan, Nathaniel, or Natalie.
-
D.
Natirar
Natirar is a historic estate and public park in Somerset County, New Jersey, known for its expansive grounds, walking trails, and luxury resort and culinary facilities.
-
E.
Na
Na is the given name of Chinese professional tennis player Li Na, a former world No. 2 and two-time Grand Slam singles champion.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7d4f88819084123ed6c9e7e5b8 |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 10, 2026, 10:34 a.m.