Triple
T2643373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The River Bank |
E62926
|
entity |
| Predicate | introducesCharacter |
P12208
|
FINISHED |
| Object | Badger |
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 | Statement: [The River Bank, introducesCharacter, Badger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Badger Context triple: [The River Bank, introducesCharacter, Badger]
-
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.
Badgers
Badgers is the nickname for the athletic teams representing the University of Wisconsin–Madison in collegiate sports.
-
C.
Porcupine
Porcupine is a historic mining community and neighborhood within the city of Timmins in northeastern Ontario, Canada.
-
D.
Wolf
Wolf is a common German surname borne by numerous notable individuals across fields such as scholarship, politics, and the arts.
-
E.
Wolf
Wolf is a song by American singer Miguel from his album "War & Leisure."
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8ff34988190ba9d69ce9d77c71d |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc02acc048190812d7d2d8b59058a |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 6, 2026, 9:53 p.m.