Triple
T4861088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IML-1 |
E108660
|
entity |
| Predicate | commander |
P1061
|
FINISHED |
| Object | Ronald J. Grabe |
E244583
|
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: Ronald J. Grabe | Statement: [IML-1, commander, Ronald J. Grabe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronald J. Grabe Context triple: [IML-1, commander, Ronald J. Grabe]
-
A.
Ronald J. Grabe
chosen
Ronald J. Grabe is a former NASA astronaut and U.S. Air Force colonel who piloted and commanded multiple Space Shuttle missions.
-
B.
Richard H. Stahlman
Richard H. Stahlman was an academic mentor and doctoral advisor known for supervising Herbert Boyer, a pioneering figure in genetic engineering and biotechnology.
-
C.
Peter T. Grauer
Peter T. Grauer is an American business executive best known as the longtime chairman of Bloomberg L.P.
-
D.
Neil A. Machlis
Neil A. Machlis is a film producer best known for his work on major Hollywood comedies, including the classic road-trip film "Planes, Trains and Automobiles."
-
E.
Ronald W. Browne
Ronald W. Browne is a film cinematographer best known for his work on the comedy western "Three Amigos."
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d5e247c8190b6ae4e9b529f0345 |
completed | March 20, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62cd028808190a61ac9c12042611f |
completed | March 27, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:26 p.m.