Triple
T12374249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Grinder |
E295081
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Fred Savage |
E387988
|
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: Fred Savage | Statement: [The Grinder, starring, Fred Savage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fred Savage Context triple: [The Grinder, starring, Fred Savage]
-
A.
Fred Savage
chosen
Fred Savage is an American actor and director best known for his childhood role as Kevin Arnold on the television series "The Wonder Years."
-
B.
Corey Feldman
Corey Feldman is an American actor and former child star best known for his roles in 1980s films such as "The Goonies," "Stand by Me," and "The Lost Boys."
-
C.
Skeet Ulrich
Skeet Ulrich is an American actor best known for his roles in films like "Scream" and "The Craft" and the television series "Jericho."
-
D.
Dylan Walsh
Dylan Walsh is an American actor best known for his role as Dr. Sean McNamara on the television series "Nip/Tuck."
-
E.
Eriq La Salle
Eriq La Salle is an American actor, director, and producer best known for his role as Dr. Peter Benton on the television series "ER."
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa8ca7c8190b3f8e9c2ec23e837 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63473efd481909b2061f3b19e1aaf |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.