Triple
T20277508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Topaz Medallion |
E503053
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object | Peter Eisenman |
—
|
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: Peter Eisenman | Statement: [Topaz Medallion, notableRecipient, Peter Eisenman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Eisenman Context triple: [Topaz Medallion, notableRecipient, Peter Eisenman]
-
A.
Peter Eisenman
chosen
Peter Eisenman is an American architect and theorist known for his deconstructivist designs and intellectually rigorous, often controversial architectural works.
-
B.
Leon Reiser
Leon Reiser is the son of American actor and comedian Paul Reiser.
-
C.
Peter Rosenbaum
Peter Rosenbaum is a cinematographer best known for his work on the 2008 coming-of-age film "The Wackness."
-
D.
Robert Engelman
Robert Engelman is a film producer known for his work on major Hollywood genre films, including action, science fiction, and fantasy projects.
-
E.
Bruce Berman
Bruce Berman is an American film producer and studio executive known for overseeing and producing numerous major Hollywood films.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e675e4cdfc81908c7cb4519a7d744b |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 16, 2026, 10:35 a.m.