Triple
T10396316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashes to Ashes |
E245030
|
entity |
| Predicate | actor |
P5563
|
FINISHED |
| Object | Marshall Lancaster |
E868915
|
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: Marshall Lancaster | Statement: [Ashes to Ashes, actor, Marshall Lancaster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marshall Lancaster Context triple: [Ashes to Ashes, actor, Marshall Lancaster]
-
A.
Marshall Lancaster
chosen
Marshall Lancaster is a British actor best known for his role as DC Chris Skelton in the television series "Life on Mars" and its sequel "Ashes to Ashes."
-
B.
Marshall Harvey
Marshall Harvey is a film editor best known for his work on movies such as the dark comedy "The 'Burbs."
-
C.
Scott Marshall
Scott Marshall is an American film and television director known for his work on comedies and for being the son of filmmaker Garry Marshall.
-
D.
Brian Marshall
Brian Marshall was a British actor known for his supporting roles in film and television, including an appearance in the crime thriller "The Long Good Friday."
-
E.
Marshall Pease
Marshall Pease is a computer scientist best known for co-authoring the seminal paper that introduced the Byzantine Generals Problem in distributed computing and fault tolerance.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9cf79348190975d6c1791e3b621 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e4aef148190be58486605f85f77 |
completed | April 10, 2026, 8:32 p.m. |
Created at: April 6, 2026, 12:06 p.m.