Triple
T10844599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean Bean |
E255978
|
entity |
| Predicate | familyName |
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: [Sean Bean, familyName, Bean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bean Context triple: [Sean Bean, familyName, Bean]
-
A.
Bean
Bean is the famous jazz saxophonist Coleman Hawkins, a pioneering tenor sax player whose rich tone and improvisational style helped define early jazz.
-
B.
Bean
chosen
Bean is a common English surname of Old English origin, associated with various notable individuals including the actor Sean Bean.
-
C.
Bean
Bean is a small village and civil parish in the borough of Dartford in north-west Kent, England.
-
D.
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.
-
E.
JavaBeans
JavaBeans is a reusable software component model for the Java platform that defines conventions for building modular, configurable Java classes, often used in visual development environments.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d750d0155c81908fb55ba6b45db800 |
completed | April 9, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7ca05788190aff4f34084499ba6 |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:19 p.m.