Triple
T837378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Back to Bedlam |
E18098
|
entity |
| Predicate | artist |
P184
|
FINISHED |
| Object | James Blunt |
E3429
|
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: James Blunt | Statement: [Back to Bedlam, artist, James Blunt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Blunt Context triple: [Back to Bedlam, artist, James Blunt]
-
A.
James Blunt
chosen
James Blunt is an English singer-songwriter and former British Army officer best known for his hit single "You're Beautiful" and the album "Back to Bedlam."
-
B.
John Mayer
John Mayer is an American singer-songwriter and virtuoso guitarist known for blending blues, rock, and pop in both chart-topping hits and acclaimed live performances.
-
C.
Michael Coulter
Michael Coulter is a British cinematographer known for his work on popular films including the romantic comedy "Love Actually."
-
D.
John Tedder
John Tedder is known primarily as the son of Arthur Tedder, the prominent British air marshal and senior Royal Air Force commander during World War II.
-
E.
Gavin DeGraw
Gavin DeGraw is an American singer-songwriter best known for his soulful pop-rock hits like "I Don't Want to Be" and "Chariot."
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abcf69888190b342363978273ae2 |
completed | March 1, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d9cddb48190b0d297c2cc9f3b3c |
completed | March 3, 2026, 11:24 p.m. |
Created at: March 1, 2026, 7:38 p.m.