Triple
T21446584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Shaffer |
E529091
|
entity |
| Predicate | adaptedFrom |
P1926
|
FINISHED |
| Object | Amadeus (play) |
E145068
|
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: Amadeus (play) | Statement: [Peter Shaffer, adaptedFrom, Amadeus (play)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amadeus (play) Context triple: [Peter Shaffer, adaptedFrom, Amadeus (play)]
-
A.
Amadeus
Amadeus is the given name of Victor Amadeus II of Savoy, an early 18th-century ruler who became the first King of Sardinia and a significant European monarch.
-
B.
Amadeus
Amadeus is a music producer known for his work on hip-hop projects such as the album "Crime Pays."
-
C.
Amadeus
chosen
Amadeus is a critically acclaimed 1984 period drama film that portrays the life and music of Wolfgang Amadeus Mozart through the jealous eyes of his rival Antonio Salieri.
-
D.
Amadeus
Amadeus is a given name most famously associated with composer Wolfgang Amadeus Mozart and used by various notable figures, including the German composer Karl Amadeus Hartmann.
-
E.
Amadeus
Amadeus is a leading global travel technology and distribution company that provides reservation, ticketing, and IT solutions for airlines, travel agencies, and other travel industry players.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9cea7bc81909ee3e1cdeda1fe7e |
completed | April 23, 2026, 9:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09c9054e0c81908f13a2240c200b9e |
completed | May 17, 2026, 1:56 p.m. |
Created at: April 16, 2026, 6:06 p.m.