Triple
T14910816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John W. Tukey |
E371254
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Exploratory Data Analysis |
E371255
|
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: Exploratory Data Analysis | Statement: [John W. Tukey, notableWork, Exploratory Data Analysis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Exploratory Data Analysis Context triple: [John W. Tukey, notableWork, Exploratory Data Analysis]
-
A.
Exploratory Data Analysis
chosen
Exploratory Data Analysis is a statistical approach, popularized by John W. Tukey, that focuses on using visual and quantitative techniques to summarize data, uncover patterns, and suggest hypotheses before formal modeling.
-
B.
The Future of Data Analysis
"The Future of Data Analysis" is a seminal 1962 paper by statistician John W. Tukey that helped define and popularize exploratory data analysis and reshaped modern statistical practice.
-
C.
Data Mining: The Textbook
Data Mining: The Textbook is a comprehensive academic book that systematically covers the principles, algorithms, and applications of data mining and knowledge discovery in databases.
-
D.
The Joy of Data
The Joy of Data is a documentary presented by mathematician Hannah Fry that explores how data shapes our world in an accessible and engaging way.
-
E.
Outlier Analysis
Outlier Analysis is a comprehensive book by Charu C. Aggarwal that systematically covers the theory, algorithms, and applications of detecting anomalous data in various domains.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded61c6b9c8190a92934d49b98fe46 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72bb366481909706d511f5ae1290 |
completed | May 8, 2026, 11:33 p.m. |
Created at: April 10, 2026, 2:26 a.m.