Triple
T921806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Bradbury |
E19900
|
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: [Ray Bradbury, familyName, Bradbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bradbury Context triple: [Ray 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.
Haldeman
Haldeman is a surname most notably associated with H. R. Haldeman, the White House Chief of Staff under U.S. President Richard Nixon and a central figure in the Watergate scandal.
-
C.
Haldeman
Haldeman is the maiden surname of model and dietitian Maye Musk, mother of entrepreneur Elon Musk.
-
D.
Richard Matheson
Richard Matheson was an American author and screenwriter renowned for his influential works of horror, science fiction, and fantasy, including the novel "I Am Legend" and numerous classic "The Twilight Zone" episodes.
-
E.
Isaac Asimov
Isaac Asimov was a prolific American science fiction author and biochemist renowned for works like the Foundation series and his popular science writing.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b313cb908190ad78b3a54e4f2eb7 |
completed | March 1, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826d8f9408190aa286bb809507797 |
completed | March 4, 2026, 12:34 p.m. |
Created at: March 1, 2026, 7:40 p.m.