Triple
T20398559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Weatherwax |
E500272
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ken Weatherwax |
—
|
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: Ken Weatherwax | Statement: [Ken Weatherwax, name, Ken Weatherwax]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Weatherwax Context triple: [Ken Weatherwax, name, Ken Weatherwax]
-
A.
Ken Weatherwax
chosen
Ken Weatherwax was an American child actor best known for playing Pugsley Addams on the 1960s television series "The Addams Family."
-
B.
Paul Weatherwax
Paul Weatherwax was an American film editor known for his work on numerous Hollywood productions from the 1930s through the 1950s, including several major studio features.
-
C.
Chris Angelico
Chris Angelico is a Python developer and community contributor known for his involvement in Python Enhancement Proposals, including co-authoring PEP 572.
-
D.
Ben Finney
Ben Finney was an anthropologist and pioneer of experimental archaeology best known for reviving traditional Polynesian navigation and co-founding the Polynesian Voyaging Society.
-
E.
David Finfer
David Finfer was an American film editor known for his work on a wide range of Hollywood movies across several decades.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6798c2b28819092fab93f01218cde |
completed | April 20, 2026, 7:07 p.m. |
Created at: April 16, 2026, 11:29 a.m.