Triple
T18740318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neil Dudgeon |
E458270
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | Pie in the Sky |
—
|
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: Pie in the Sky | Statement: [Neil Dudgeon, appearedIn, Pie in the Sky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pie in the Sky Context triple: [Neil Dudgeon, appearedIn, Pie in the Sky]
-
A.
Pie in the Sky
chosen
Pie in the Sky is a British television drama-comedy series about a detective who balances police work with running his own restaurant.
-
B.
Sky in the Pie
Sky in the Pie is a humorous and imaginative children's poetry collection by British poet Roger McGough.
-
C.
Pi in the Sky
Pi in the Sky is a popular science book by cosmologist John D. Barrow that explores the nature of mathematics and its deep connections to the physical universe.
-
D.
Hot Pie
Hot Pie is a minor character in the "A Song of Ice and Fire" novels and the "Game of Thrones" TV series, known as a former orphan and traveling companion of Arya Stark who becomes a baker.
-
E.
The Pie
The Pie is the spirited horse ridden by Velvet Brown in the classic novel and film "National Velvet."
- 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5768d6a208190817abe904fab433b |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 10, 2026, 11:51 a.m.