Triple
T21104746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hel Helson |
E520009
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Paul Bunyan |
—
|
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: Paul Bunyan | Statement: [Hel Helson, associatedWith, Paul Bunyan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Bunyan Context triple: [Hel Helson, associatedWith, Paul Bunyan]
-
A.
Paul Bunyan
Paul Bunyan is a 1941 operetta by Benjamin Britten, with a libretto by W. H. Auden, based on the American folk legend of the giant lumberjack.
-
B.
Paul Bunyan (American folk legend)
chosen
Paul Bunyan is a giant lumberjack of American folklore, famed for his superhuman strength, colossal blue ox Babe, and tall tales explaining natural landmarks across North America.
-
C.
John Big Tree
John Big Tree was a Seneca Native American actor best known for his roles in early 20th-century Hollywood Western films.
-
D.
Karl the Giant
Karl the Giant is a towering, gentle circus performer in the film "Big Fish," known for his immense size and kind-hearted friendship with the protagonist.
-
E.
Bart the Bear
Bart the Bear was a famous trained Kodiak bear actor known for his prominent roles in Hollywood films and television.
- 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_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b6150f08190a3738f1eda7fa834 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 2:53 p.m.