Triple
T13807689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerald Loeb Award |
E331802
|
entity |
| Predicate | founder |
P104
|
FINISHED |
| Object | Gerald Loeb |
E1062760
|
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: Gerald Loeb | Statement: [Gerald Loeb Award, founder, Gerald Loeb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerald Loeb Context triple: [Gerald Loeb Award, founder, Gerald Loeb]
-
A.
Gerald Loeb
chosen
Gerald Loeb was a prominent American stockbroker, financial writer, and co-founder of E.F. Hutton, renowned for his influential investment advice and market commentary.
-
B.
Alfred E. Kahn
Alfred E. Kahn was an American economist and regulator best known as the chief architect of U.S. airline deregulation in the late 1970s.
-
C.
Solomon Loeb
Solomon Loeb was a prominent 19th-century German-American banker and co-founder of the influential investment bank Kuhn, Loeb & Co.
-
D.
Irving Glassberg
Irving Glassberg was a Polish-born American cinematographer known for his work on numerous Universal Pictures films in the 1940s and 1950s.
-
E.
Edgar M. Kahn
Edgar M. Kahn was an American neurosurgeon and academic known for his contributions to the development of neurosurgical techniques and education in the mid-20th century.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026eae8481908b8880635e6a9152 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8dc1ec0819098c4f32eb3991613 |
completed | May 3, 2026, 9:06 p.m. |
Created at: April 9, 2026, 10:12 p.m.