Triple
T2640569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union |
E62854
|
entity |
| Predicate | chairman |
P377
|
FINISHED |
| Object | Jay Sugarman |
E150126
|
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: Jay Sugarman | Statement: [Union, chairman, Jay Sugarman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Sugarman Context triple: [Union, chairman, Jay Sugarman]
-
A.
Jay Sugarman
chosen
Jay Sugarman is an American businessman and real estate investor best known as the owner and chairman of Major League Soccer’s Philadelphia Union.
-
B.
Nathan Sugarman
Nathan Sugarman was an American physicist known for his work in nuclear chemistry and his contributions to the Manhattan Project.
-
C.
Johnny Gandelsman
Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
-
D.
Sam Jaffe
Sam Jaffe was an American actor and character performer known for memorable roles in classic films such as "Gunga Din," "The Asphalt Jungle," and "Ben-Hur."
-
E.
Steven Baigelman
Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8fc8ee881908a9f6820d8934a62 |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4881323dc81908e3e42ce1d0f8a0d |
completed | March 13, 2026, 9:56 p.m. |
Created at: March 6, 2026, 9:53 p.m.