Triple
T258801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adler Planetarium |
E5495
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Max Adler |
E78930
|
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: Max Adler | Statement: [Adler Planetarium, namedAfter, Max Adler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Max Adler Context triple: [Adler Planetarium, namedAfter, Max Adler]
-
A.
Max Adler
chosen
Max Adler was an American businessman and philanthropist best known for founding Chicago’s Adler Planetarium, the first planetarium in the Western Hemisphere.
-
B.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
-
C.
Charles Weissmann
Charles Weissmann is a Swiss molecular biologist and biotechnology pioneer known for his groundbreaking work on interferons and prion diseases and for co-founding the biotech company Biogen.
-
D.
Sam Zussman
Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
-
E.
Chris Lebenzon
Chris Lebenzon is an American film editor known for his long-time collaborations with directors like Tim Burton and Tony Scott on major Hollywood films.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d71a10c8190894c86e7a67c5974 |
completed | Feb. 28, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56c475ce88190bf16e5ee76f1d3b5 |
completed | March 2, 2026, 10:53 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.