Triple
T12209652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Brown |
E290921
|
entity |
| Predicate | livesWith |
P4704
|
FINISHED |
| Object | Jonathan Brown |
E971834
|
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: Jonathan Brown | Statement: [Mr. Brown, livesWith, Jonathan Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Brown Context triple: [Mr. Brown, livesWith, Jonathan Brown]
-
A.
Jonathan Brown
Jonathan Brown is a cinematographer best known for his work on major studio comedies and mainstream Hollywood films, including the 2006 reboot of The Pink Panther.
-
B.
Jonathan Brown
chosen
Jonathan Brown is an individual known primarily as the son of Mr. Brown.
-
C.
Russ Brown
Russ Brown was an American actor best known for his Tony Award–winning performance as the original coach Van Buren in the Broadway musical "Damn Yankees."
-
D.
Andrew Brown
Andrew Brown is a songwriter credited with co-writing the track "Stop and Stare."
-
E.
Anthony Gregory Brown
Anthony Gregory Brown is an American politician and attorney who has served as Maryland's Attorney General and previously as the state's lieutenant governor and a U.S. Representative.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c7ed4688190b0546b784e36b0ec |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a8c69308190bffae7b38cc5620b |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:51 p.m.