Triple
T16222227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henderson |
E393755
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Bill Henderson |
E668180
|
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: Bill Henderson | Statement: [Henderson, hasNotableBearer, Bill Henderson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Henderson Context triple: [Henderson, hasNotableBearer, Bill Henderson]
-
A.
Bill Henderson
chosen
Bill Henderson was an American jazz vocalist and character actor known for his rich baritone voice and numerous film and television appearances.
-
B.
Wayne Henderson
Wayne Henderson was an American jazz trombonist, composer, and record producer best known as a founding member of The Jazz Crusaders and for his influential work in soul-jazz and jazz-funk.
-
C.
Cal Henderson
Cal Henderson is a British software engineer and entrepreneur best known as the co-founder and CTO of the workplace communication platform Slack.
-
D.
William Henderson
William Henderson was an early settler and landowner after whom the town of Henderson in Jefferson County, New York, was named.
-
E.
Michael Henderson
Michael Henderson is an author best known for writing the book "Window Seat."
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e227fcf058819099d5ff965cc2c267 |
completed | April 17, 2026, 12:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ed55a7c8190b4bc8bc325a5da5b |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:03 a.m.