Triple
T6991915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBadger |
E162104
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Badger (The Wind in the Willows) |
E285185
|
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: Badger (The Wind in the Willows) | Statement: [MacBadger, basedOn, Badger (The Wind in the Willows)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Badger (The Wind in the Willows) Context triple: [MacBadger, basedOn, Badger (The Wind in the Willows)]
-
A.
Badger
chosen
Badger is a wise, kind, and somewhat reclusive character from Kenneth Grahame’s "The Wind in the Willows," known for offering guidance and shelter to his woodland friends.
-
B.
Badger
Badger is a fictional character appearing in the work "The Return of Ulysses."
-
C.
Badger
Badger is the NATO reporting name for the Soviet-era Tupolev Tu-16, a twin-engine jet strategic bomber widely used during the Cold War.
-
D.
Badger
Badger is a British rock band best known for its early-1970s progressive rock sound and connections to members of the band Yes.
-
E.
Badger
Badger is a small town in central Newfoundland and Labrador, Canada, known historically for its logging industry and proximity to the Exploits River.
- 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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbc1f63c8190837cfd71cf5ed613 |
completed | March 27, 2026, 7:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a161f088190bbc3c4e2815fa929 |
completed | March 28, 2026, 5:41 a.m. |
Created at: March 27, 2026, 2:32 p.m.