Triple
T16999237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Perretta |
E412395
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Weatherman |
E838153
|
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: The Weatherman | Statement: [Michael Perretta, notableWork, The Weatherman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Weatherman Context triple: [Michael Perretta, notableWork, The Weatherman]
-
A.
The Weatherman
chosen
The Weatherman is a component or segment within the larger work "History Books," likely serving as a distinct chapter, story, or track that contributes to the overall narrative or theme.
-
B.
The Weather Man
The Weather Man is a 2005 dark comedy-drama film starring Nicolas Cage as a troubled Chicago TV weatherman struggling with family and personal crises.
-
C.
Weatherman
Weatherman is a track by rapper and producer J Dilla, featured on his posthumous album "The Shining."
-
D.
Strange Weather
Strange Weather is a collection of four horror and dark fantasy novellas by Joe Hill that explore unsettling, supernatural twists on everyday life.
-
E.
Fair Weather
"Fair Weather" is a cool jazz track famously performed by trumpeter Chet Baker on his album *Chet Baker in New York*.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d37cd6248190a7202ae754882640 |
completed | April 18, 2026, 6:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc1ac518819093fac61b5598d730 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:32 a.m.