Triple
T17564884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honey, I Shrunk the Kids |
E427784
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Ron Thompson |
—
|
NE NERFINISHED |
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: Ron Thompson | Statement: [Honey, I Shrunk the Kids, mainCharacter, Ron Thompson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ron Thompson Context triple: [Honey, I Shrunk the Kids, mainCharacter, Ron Thompson]
-
A.
Ron Thompson
chosen
Ron Thompson is a fictional character best known as one of the kids in the 1989 science-fiction family film "Honey, I Shrunk the Kids."
-
B.
Carl Thompson
Carl Thompson is a songwriter best known for co-writing the R&B track "Soon as I Get Home."
-
C.
Donald Thompson
Donald Thompson is a fictional police lieutenant and the father of Nancy Thompson in the horror film "A Nightmare on Elm Street."
-
D.
Don Thompson
Don Thompson is an actor known for his role in the horror-comedy film "Slither."
-
E.
Larry Thompson
Larry Thompson is an American lawyer and former U.S. Deputy Attorney General known for his leadership in corporate and white-collar crime enforcement.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4592ce42c8190a54a0a328c5e8ffc |
completed | April 19, 2026, 4:25 a.m. |
Created at: April 10, 2026, 5:50 a.m.