Triple
T9080964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malcolm Bradbury |
E217620
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bradbury |
E19900
|
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: Bradbury | Statement: [Malcolm Bradbury, familyName, Bradbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bradbury Context triple: [Malcolm Bradbury, familyName, Bradbury]
-
A.
Ray Bradbury
chosen
Ray Bradbury was an American author best known for his imaginative and socially critical science fiction and fantasy works, including the classic novel "Fahrenheit 451."
-
B.
Bradbury and Evans
Bradbury and Evans was a prominent 19th-century London publishing and printing firm best known for producing works by Charles Dickens and other major Victorian authors.
-
C.
David Bradbury
David Bradbury is known primarily as the son of American physicist and former Los Alamos Laboratory director Norris Bradbury.
-
D.
Daniel Keyes
Daniel Keyes was an American author best known for his science fiction work "Flowers for Algernon," which explores themes of intelligence, identity, and human dignity.
-
E.
Philip K. Dick
Philip K. Dick was an American science fiction author renowned for his philosophical, reality-bending stories that inspired numerous films, including the one on which "The Adjustment Bureau" is based.
- 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_69ca83d7a0388190ba1af89ed7ba36f9 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9607942c8190a21620892ce3cbe5 |
completed | April 1, 2026, 3:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffe28ae548190924cc7bbf453f3f3 |
completed | April 3, 2026, 5:51 p.m. |
Created at: March 30, 2026, 7:13 p.m.