Triple

T1383054
Position Surface form Disambiguated ID Type / Status
Subject Emmy Noether Lecture E29381 entity
Predicate hasNotableLecturer P21690 FINISHED
Object Ingrid Daubechies E62072 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: Ingrid Daubechies | Statement: [Emmy Noether Lecture, hasNotableLecturer, Ingrid Daubechies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ingrid Daubechies
Context triple: [Emmy Noether Lecture, hasNotableLecturer, Ingrid Daubechies]
  • A. Ingrid Daubechies chosen
    Ingrid Daubechies is a Belgian physicist and mathematician renowned for her pioneering work in wavelet theory and its applications to signal processing, image compression, and data analysis.
  • B. Charles Fefferman
    Charles Fefferman is an American mathematician renowned for his groundbreaking work in harmonic analysis, partial differential equations, and several complex variables, and is a Fields Medalist and long-time professor at Princeton University.
  • C. Johannes Eisermann
    Johannes Eisermann is a scholar known for his professorship at the European University Viadrina in Frankfurt (Oder), where he has made notable academic contributions.
  • D. John W. Tukey
    John W. Tukey was an influential American mathematician and statistician best known for coining the term "bit," developing exploratory data analysis, and creating the box plot and the Fast Fourier Transform (FFT) algorithm.
  • E. Emanuel Parzen
    Emanuel Parzen was an American statistician renowned for pioneering kernel density estimation, particularly through the development of the Parzen window method.
  • 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_69a498d883a48190bfdca525296ef7ee completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c48ff58c8190aeaf09d3e7cad7c7 completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd48c41f4819092f7e1302d803662 completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:59 p.m.