Triple
T8448043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke Grimes |
E199728
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Luke Grimes |
E199728
|
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: Luke Grimes | Statement: [Luke Grimes, name, Luke Grimes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luke Grimes Context triple: [Luke Grimes, name, Luke Grimes]
-
A.
Luke Grimes
chosen
Luke Grimes is an American actor known for his roles in films like the Fifty Shades series and the television drama Yellowstone.
-
B.
Colin Donnell
Colin Donnell is an American actor best known for his television roles in series such as "Arrow" and "Chicago Med," as well as his work on Broadway.
-
C.
Joe Maross
Joe Maross was an American character actor known for his numerous film and television roles from the 1950s through the 1980s, including appearances in classic series like "The Twilight Zone."
-
D.
Joel Courtney
Joel Courtney is an American actor best known for his breakout role in the science-fiction film "Super 8" and later appearances in projects such as "The Kissing Booth" series.
-
E.
Barry Corbin
Barry Corbin is an American character actor known for his roles in films like Urban Cowboy and WarGames and TV series such as Northern Exposure.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44480ec8190b32443a53cd4f943 |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1dbf2e2c8190b20e842438acb4d5 |
completed | April 2, 2026, 7:41 a.m. |
Created at: March 30, 2026, 6:09 p.m.