Triple
T15368235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mini's First Time |
E367470
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Marshall Harvey |
E404669
|
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 Harvey | Statement: [Mini's First Time, editedBy, Marshall Harvey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marshall Harvey Context triple: [Mini's First Time, editedBy, Marshall Harvey]
-
A.
Marshall Harvey
chosen
Marshall Harvey is a film editor best known for his work on movies such as the dark comedy "The 'Burbs."
-
B.
Marshall Lancaster
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."
-
C.
Harvey Harrison
Harvey Harrison is a cinematographer known for his work on feature films, including the 1986 drama "Castaway."
-
D.
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.
-
E.
Marshall Thompson
Marshall Thompson was an American film and television actor best known for his roles in mid-20th-century Hollywood productions, including war dramas and science fiction films.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4a7cdc8190b7b48c97e774c306 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb0319f248190a37c9afa09c32428 |
completed | May 9, 2026, 10:07 p.m. |
Created at: April 10, 2026, 3:18 a.m.