Triple
T14237319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steven Meigs Ford |
E352916
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Michael Gerald Ford |
E346945
|
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 Gerald Ford | Statement: [Steven Meigs Ford, relative, Michael Gerald Ford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Gerald Ford Context triple: [Steven Meigs Ford, relative, Michael Gerald Ford]
-
A.
Michael Gerald Ford
chosen
Michael Gerald Ford is the eldest son of former U.S. President Gerald Ford and First Lady Betty Ford, known for his low-profile public life and work in banking and nonprofit organizations.
-
B.
Michael Ford
Michael Ford is an actor known for his role in the film "The Little People."
-
C.
Daniel Ford
Daniel Ford was a 19th-century American editor and publisher best known for shaping the influential family magazine The Youth's Companion.
-
D.
Fred Ford
Fred Ford is a video game designer and programmer best known as the co-creator of the Star Control series and co-founder of the game development studio Toys for Bob.
-
E.
David M. Ford
David M. Ford is best known as the former husband of American actress and model Cybill Shepherd.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de62422e28819089e7115052a28c96 |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3253fc2c8190ba2da6fe6a910d85 |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:07 a.m.