Triple
T21488115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pittsburgh Symphony Orchestra |
E530165
|
entity |
| Predicate | formerMusicDirector |
P255
|
FINISHED |
| Object | Marek Janowski |
—
|
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: Marek Janowski | Statement: [Pittsburgh Symphony Orchestra, formerMusicDirector, Marek Janowski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marek Janowski Context triple: [Pittsburgh Symphony Orchestra, formerMusicDirector, Marek Janowski]
-
A.
Marek Janowski
chosen
Marek Janowski is a renowned Polish-born German conductor particularly celebrated for his interpretations of the German Romantic and Wagnerian operatic repertoire.
-
B.
Marek Lipski
Marek Lipski is an individual notable enough to be recognized as a bearer of the surname Lipski, though specific widely known public details about him are not readily available.
-
C.
Marek Zaleski
Marek Zaleski is a Polish literary critic and essayist known for his work on modern Polish literature and literary theory.
-
D.
Marek Piekarski
Marek Piekarski is a Polish former footballer known for playing as a midfielder in the 1970s and 1980s.
-
E.
Marek Morzyński
Marek Morzyński is a researcher in fluid dynamics and flow control, known for his collaborative work on reduced-order modeling and aerodynamic applications.
- 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea390bd88190bc444e6af275f6e8 |
completed | April 23, 2026, 9:45 a.m. |
Created at: April 16, 2026, 6:22 p.m.