Triple
T10097047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glover |
E215895
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | John Glover (actor) |
E377389
|
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: John Glover (actor) | Statement: [Glover, hasNotableBearer, John Glover (actor)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Glover (actor) Context triple: [Glover, hasNotableBearer, John Glover (actor)]
-
A.
John Glover
John Glover was an American Revolutionary War officer and mariner best known for leading the Marblehead Regiment and helping George Washington cross the Delaware River.
-
B.
John Glover
chosen
John Glover is an American character actor known for his versatile roles in film, television, and theater, including memorable performances in projects like "Smallville" and "Batman & Robin."
-
C.
John Ehle
John Ehle was an American novelist and screenwriter best known for his historical fiction set in the Appalachian region of North Carolina.
-
D.
John Grover
John Grover is a film editor best known for his work on action and thriller movies, including the James Bond film series.
-
E.
Oliver Hudson
Oliver Hudson is an American actor known for his roles in television series such as "Rules of Engagement," "Nashville," and "Scream Queens."
- 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_69ca83a4947c8190823a7495dc5d96ed |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd07ad40081909610a7a8dc836651 |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b6c218b08190853b0979296e2f83 |
completed | April 5, 2026, 7:23 p.m. |
Created at: March 30, 2026, 9:02 p.m.