Triple
T20286881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oliver Milburn |
E509903
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Wycliffe |
—
|
NE NERFINISHED |
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: Wycliffe | Statement: [Oliver Milburn, notableWork, Wycliffe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wycliffe Context triple: [Oliver Milburn, notableWork, Wycliffe]
-
A.
Wycliffe
chosen
Wycliffe is a British television crime drama series centered on Detective Superintendent Charles Wycliffe as he investigates complex cases in Cornwall.
-
B.
Walkelin
Walkelin was an 11th-century Norman cleric who became the first Norman Bishop of Winchester and oversaw the construction of its great Romanesque cathedral.
-
C.
Welchman
Welchman is a surname most notably associated with Gordon Welchman, a key British codebreaker at Bletchley Park during World War II.
-
D.
Hawise
Hawise is a medieval European female given name borne by several noblewomen in England and France.
-
E.
Bygrave
Bygrave is a small rural village in the North Hertfordshire district of Hertfordshire, England, known for its historic church and surrounding farmland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e676931fe08190b278d829a745701f |
completed | April 20, 2026, 6:55 p.m. |
Created at: April 16, 2026, 11:07 a.m.