Triple
T2863349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bomis |
E63377
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Michael Davis |
E334761
|
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 Davis | Statement: [Bomis, foundedBy, Michael Davis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Davis Context triple: [Bomis, foundedBy, Michael Davis]
-
A.
Michael Davis
chosen
Michael Davis is an entrepreneur best known as a co-founder of Bomis, the web portal company that played a key role in the early development of Wikipedia.
-
B.
Michael Rogers
Michael Rogers is a relatively common personal name shared by multiple individuals across fields such as politics, sports, and the arts, rather than referring to one singular widely recognized figure.
-
C.
Michael Potts
Michael Potts is an American actor known for his work in film, television, and theater, including notable roles in projects like "The Wire," "True Detective," and various Broadway productions.
-
D.
Steven Dillingham
Steven Dillingham is an American government official who served as Director of the U.S. Census Bureau during the 2020 United States census.
-
E.
Alan Osbiston
Alan Osbiston was a British film editor known for his work on notable mid-20th-century films, including major war and drama productions.
- 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfb6e6988190b832ee05d8420633 |
completed | March 7, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38ba5bc088190bd656c2959cdfb6a |
completed | March 13, 2026, 3:59 a.m. |
Created at: March 6, 2026, 10:02 p.m.