Triple
T26599401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Einstein on the Beach |
E667586
|
entity |
| Predicate | MetropolitanOperaPremiereCity |
P161046
|
FINISHED |
| Object | New York City |
—
|
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: New York City | Statement: [Einstein on the Beach, MetropolitanOperaPremiereCity, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MetropolitanOperaPremiereCity Context triple: [Einstein on the Beach, MetropolitanOperaPremiereCity, New York City]
-
A.
MetropolitanOperaPremiereYear
Indicates the year in which a work was first premiered by the Metropolitan Opera.
-
B.
madeMetropolitanOperaDebut
Indicates that an individual gave their first performance at the Metropolitan Opera.
-
C.
operaHouseOfPremiere
Indicates the opera house where a particular work was first premiered or originally performed.
-
D.
originalBroadwayCity
Indicates the city where a theatrical production first opened on Broadway.
-
E.
preBroadwayCity
Indicates the city where a production was staged or developed prior to its official Broadway run.
- F. None of above. chosen
Provenance (4 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_69ee9cfc385081909ac9ae178030a06e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6156e79bc81908d1ab2dd5b4917aa |
completed | May 2, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f60f24ed608190bffe6c6084fc2f7a |
completed | May 2, 2026, 2:50 p.m. |
Created at: April 27, 2026, 2:11 a.m.