Triple
T12021169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myron Scholes |
E286150
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Scholes |
E286150
|
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: Scholes | Statement: [Myron Scholes, familyName, Scholes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scholes Context triple: [Myron Scholes, familyName, Scholes]
-
A.
Sedol
Sedol is the given name of Lee Sedol, the renowned South Korean professional Go player known for his historic matches against AI.
-
B.
Fischer Black
Fischer Black was an American economist and financial theorist best known for co-developing the Black–Scholes option pricing model, a foundational tool in modern quantitative finance.
-
C.
Tobin
Tobin is the given name of Tobin Heath, an American professional soccer player and multiple-time FIFA Women's World Cup champion.
-
D.
Bachelier
Bachelier was a prominent 19th-century French publishing house known for issuing influential scientific and philosophical works.
-
E.
Myron Scholes
chosen
Myron Scholes is a Canadian-American economist and Nobel laureate best known for co-developing the Black–Scholes option pricing model, a foundational tool in modern financial economics.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903ed15408190afc21afd57d6a737 |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48b62cad8819092beb72c604a4762 |
completed | May 1, 2026, 11:15 a.m. |
Created at: April 8, 2026, 9:47 p.m.