Triple
T12702168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lotfi A. Zadeh |
E303488
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Zadeh |
E62372
|
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: Zadeh | Statement: [Lotfi A. Zadeh, familyName, Zadeh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zadeh Context triple: [Lotfi A. Zadeh, familyName, Zadeh]
-
A.
Lotfi A. Zadeh
chosen
Lotfi A. Zadeh was an Azerbaijani-American computer scientist and electrical engineer best known for founding fuzzy logic and making pioneering contributions to systems theory and artificial intelligence.
-
B.
Emanuel Parzen
Emanuel Parzen was an American statistician renowned for pioneering kernel density estimation, particularly through the development of the Parzen window method.
-
C.
Norbert Wiener
Norbert Wiener was an American mathematician and philosopher best known as the founder of cybernetics and for his pioneering work in stochastic processes and harmonic analysis.
-
D.
Lotfi
Lotfi is the given name of Lotfi A. Zadeh, the Azerbaijani-American computer scientist best known as the founder of fuzzy logic.
-
E.
Edward Feigenbaum
Edward Feigenbaum is an American computer scientist known as the "father of expert systems" for his pioneering work in artificial intelligence and knowledge-based systems.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961f0941081908a879cde0be48667 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671b27790819085f0f03af33f8f21 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:22 p.m.