Triple
T18285334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wasserstein |
E437966
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Bruce Wasserstein |
—
|
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: Bruce Wasserstein | Statement: [Wasserstein, usedBy, Bruce Wasserstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bruce Wasserstein Context triple: [Wasserstein, usedBy, Bruce Wasserstein]
-
A.
Bruce Wasserstein
chosen
Bruce Wasserstein was a prominent American investment banker and dealmaker, best known for his leadership at Lazard and his major role in shaping modern Wall Street mergers and acquisitions.
-
B.
Marc Rosenthal
Marc Rosenthal is an American illustrator and cartoonist known for his humorous, retro-style artwork in children’s books and magazines.
-
C.
James Kantor
James Kantor was a South African attorney who became notable for his controversial arrest and prosecution alongside anti-apartheid activists during the Rivonia Trial.
-
D.
Edwin Schlossberg
Edwin Schlossberg is an American designer, artist, and author known for his innovative work in interactive museum and exhibition design.
-
E.
Josh Stolberg
Josh Stolberg is an American filmmaker and screenwriter known for writing horror and thriller films, including entries in the Saw franchise such as "Jigsaw."
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500f913d48190b41a1e37ca05e8b1 |
completed | April 19, 2026, 4:21 p.m. |
Created at: April 10, 2026, 10:35 a.m.