Triple
T11818818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serpico |
E281071
|
entity |
| Predicate | basedOnAuthor |
P2806
|
FINISHED |
| Object | Peter Maas |
E489032
|
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: Peter Maas | Statement: [Serpico, basedOnAuthor, Peter Maas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Maas Context triple: [Serpico, basedOnAuthor, Peter Maas]
-
A.
Peter Maas
chosen
Peter Maas was an American journalist and bestselling author known for his nonfiction crime books and biographies, including the work that inspired the film "King of the Gypsies."
-
B.
Peyo
Peyo was a Belgian cartoonist best known for creating the comic series that introduced the Smurfs.
-
C.
Paul Menzel
Paul Menzel is a relatively obscure individual whose specific public notability is not clearly established from the given information.
-
D.
Michael Ernst
Michael Ernst is a computer scientist known for his work in software engineering and programming languages, including research on type systems and software reliability.
-
E.
David Shrigley
David Shrigley is a British visual artist known for his darkly humorous, cartoon-like drawings, sculptures, and installations that blend absurdity with everyday observations.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5e760988190b50d13bba5ef5b43 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f131cbf9708190ba8394fb3508b975 |
completed | April 28, 2026, 10:16 p.m. |
Created at: April 8, 2026, 9:42 p.m.