Triple
T13510135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Contact |
E321116
|
entity |
| Predicate | cinematographer |
P1953
|
FINISHED |
| Object | Don Burgess |
E273079
|
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: Don Burgess | Statement: [Contact, cinematographer, Don Burgess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Burgess Context triple: [Contact, cinematographer, Don Burgess]
-
A.
Don Burgess
chosen
Don Burgess is an American cinematographer best known for his Oscar-nominated work on the film "Forrest Gump" and his frequent collaborations with director Robert Zemeckis.
-
B.
Ray Colcord
Ray Colcord was an American record producer and composer best known for his work in rock music and for scoring numerous television shows.
-
C.
Ray Cusick
Ray Cusick was a British designer best known for creating the iconic look of the Daleks in the long-running science fiction television series Doctor Who.
-
D.
Gene Harrogate
Gene Harrogate is a comic, hapless young drifter in Cormac McCarthy’s novel "Suttree," known for his bizarre schemes and naive optimism amid the book’s grim setting.
-
E.
Ted Daughety
Ted Daughety is an American physician and pulmonologist best known as the husband of Kansas Governor Laura Kelly.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf86a6208190be8c18f7a0158f23 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5da6a2081909dcc9785598e1196 |
completed | May 9, 2026, 7:44 a.m. |
Created at: April 9, 2026, 9:43 p.m.