Triple
T14341947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Shneiderman |
E355625
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ben Shneiderman |
E355625
|
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: Ben Shneiderman | Statement: [Ben Shneiderman, name, Ben Shneiderman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ben Shneiderman Context triple: [Ben Shneiderman, name, Ben Shneiderman]
-
A.
Ben Shneiderman
chosen
Ben Shneiderman is a pioneering computer scientist and human-computer interaction researcher known for foundational work on user interface design and information visualization.
-
B.
Bill Buxton
Bill Buxton is a pioneering computer scientist and designer known for his influential work in human-computer interaction, input technologies, and user experience design.
-
C.
Donald A. Norman
Donald A. Norman is a cognitive scientist and design theorist best known for his influential work on user-centered design and the psychology of everyday objects.
-
D.
Mark Weiser
Mark Weiser was an American computer scientist best known as the pioneering visionary of ubiquitous computing, whose ideas profoundly shaped the future of human-computer interaction.
-
E.
Steven K. Feiner
Steven K. Feiner is a computer scientist known for his pioneering work in computer graphics and augmented reality, including influential textbooks and research on user interfaces and visualization.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e87febc8190a63c668cbd0fd713 |
completed | April 14, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd469bc538819099ed5b7061cf140d |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:14 a.m.