Triple
T12137846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toad |
E289106
|
entity |
| Predicate | friend |
P8712
|
FINISHED |
| Object | Mole |
E62920
|
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: Mole | Statement: [Toad, friend, Mole]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mole Context triple: [Toad, friend, Mole]
-
A.
Mole
chosen
Mole is a gentle, home-loving animal and one of the central protagonists in Kenneth Grahame’s classic children’s novel *The Wind in the Willows*, known for his friendship with Rat, Toad, and Badger.
-
B.
Mause
Mause is a character in Allan Ramsay’s pastoral play "The Gentle Shepherd," typically depicted as an old, wise woman who provides comic relief and guidance.
-
C.
Rato
Rato is the central protagonist of the story "Trash," around whom the narrative and its events primarily revolve.
-
D.
Hérisson
Hérisson is the French nickname for Marcel Duchamp’s influential readymade sculpture "Bottle Rack," a seminal work in the development of conceptual art.
-
E.
Mossie
Mossie is the popular nickname for the British de Havilland Mosquito NF Mk II night fighter aircraft used during World War II.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9158dd00c819082651891898b91bb |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a81f6708190a6a215421f8ce8dd |
completed | May 2, 2026, 4:46 p.m. |
Created at: April 8, 2026, 9:49 p.m.