Triple
T15168260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katherine LaNasa |
E362415
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Grant Show |
E1046662
|
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: Grant Show | Statement: [Katherine LaNasa, spouse, Grant Show]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grant Show Context triple: [Katherine LaNasa, spouse, Grant Show]
-
A.
Grant Show
chosen
Grant Show is an American actor best known for his role as Jake Hanson on the 1990s television series "Melrose Place."
-
B.
David Gale
David Gale was an American mathematician and economist known for his influential work in game theory, mathematical economics, and the theory of linear programming.
-
C.
David Gale
David Gale is a film producer best known for his work on the science fiction action movie "Æon Flux."
-
D.
David Gale
David Gale is a film producer best known for his work on the inspirational basketball drama "Coach Carter."
-
E.
The Cho Show
The Cho Show is a reality television series that follows comedian Margaret Cho’s personal and professional life with her trademark candid humor and social commentary.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0064dba588190a4341775b472a6d3 |
completed | April 15, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec889c3408190bdfc75ce72dd5a62 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:08 a.m.