Triple
T7272212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Understanding Human History |
E161133
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Michael H. Hart |
E31697
|
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: Michael H. Hart | Statement: [Understanding Human History, author, Michael H. Hart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael H. Hart Context triple: [Understanding Human History, author, Michael H. Hart]
-
A.
Michael H. Hart
chosen
Michael H. Hart is an American astrophysicist and author best known for his work on the Fermi paradox and his controversial book "The 100: A Ranking of the Most Influential Persons in History."
-
B.
Michael S. Hart
Michael S. Hart was an American author and digital pioneer best known for creating Project Gutenberg, the first and largest digital library of free eBooks.
-
C.
Michael Hart
Michael Hart was the founder of Project Gutenberg and a pioneer of digital libraries and e-books.
-
D.
Hercules Linton
Hercules Linton was a 19th-century Scottish shipbuilder and naval architect best known for designing the famous tea clipper Cutty Sark.
-
E.
John Victor-Smith
John Victor-Smith is a film editor best known for his work on major feature films including the superhero movie "Superman III."
- 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb0a03888190b5aa1da80dd303c5 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e52f96008190886f6115329a07ab |
completed | March 28, 2026, 2:26 p.m. |
Created at: March 27, 2026, 2:58 p.m.