Triple
T7598491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William George Bean |
E179919
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Bean |
E255978
|
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: Bean | Statement: [William George Bean, hasFamilyName, Bean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bean Context triple: [William George Bean, hasFamilyName, Bean]
-
A.
Bean
chosen
Bean is a common English surname of Old English origin, associated with various notable individuals including the actor Sean Bean.
-
B.
Bean
Bean is a 1997 British-American comedy film based on Rowan Atkinson’s Mr. Bean character, following his chaotic misadventures in the United States.
-
C.
Bean
Bean is the famous jazz saxophonist Coleman Hawkins, a pioneering tenor sax player whose rich tone and improvisational style helped define early jazz.
-
D.
The Bean
The Bean is a famous stainless steel public sculpture by artist Anish Kapoor located in Chicago’s Millennium Park, renowned for its highly polished, reflective surface and iconic, bean-like shape.
-
E.
BEA
BEA is a U.S. government agency that produces key economic statistics, including measures of national income, output, and growth.
- 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_69c69f3487ec8190bf7acdf2dd91e6d6 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9d67cf88190a3202c07f7cea7df |
completed | March 27, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c861a7a7088190ba8d72e63f4dcaa0 |
completed | March 28, 2026, 11:17 p.m. |
Created at: March 27, 2026, 3:53 p.m.