Triple
T10147738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael S. Turner |
E231747
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael S. Turner |
E231747
|
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 S. Turner | Statement: [Michael S. Turner, name, Michael S. Turner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael S. Turner Context triple: [Michael S. Turner, name, Michael S. Turner]
-
A.
Michael S. Turner
chosen
Michael S. Turner is an American cosmologist and astrophysicist known for pioneering work on dark energy, inflation, and the early universe.
-
B.
James Whitaker
James Whitaker is a film cinematographer known for his work on feature films such as the comedy-drama "Troop Zero."
-
C.
Navin R. Johnson
Navin R. Johnson is the naive, bumbling protagonist of the 1979 comedy film "The Jerk," famously portrayed by Steve Martin.
-
D.
Jim Kripps
Jim Kripps is a fictional character appearing in the work titled "The Silence."
-
E.
William D. Ford
William D. Ford was a long-serving U.S. Congressman from Michigan known for his work on education, labor rights, and student financial aid legislation.
- 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_69ca848364f881908a24366a6feec1db |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec011c24819089b456fc8b9ed80c |
completed | April 2, 2026, 4:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3009992388190ab2a4aee23d0e004 |
completed | April 6, 2026, 12:38 a.m. |
Created at: March 30, 2026, 9:07 p.m.