Triple
T18846520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fauna Japonica |
E460930
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Fauna Japonica: Pisces |
—
|
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: Fauna Japonica: Pisces | Statement: [Fauna Japonica, hasPart, Fauna Japonica: Pisces]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fauna Japonica: Pisces Context triple: [Fauna Japonica, hasPart, Fauna Japonica: Pisces]
-
A.
Fauna Japonica
chosen
Fauna Japonica is a landmark 19th-century zoological work that systematically documented and illustrated the animal species of Japan for a European scientific audience.
-
B.
Fauna
Fauna is one of the three good fairies in Disney's "Sleeping Beauty," known for her gentle, nurturing nature and green attire.
-
C.
Fauna
Fauna is a Roman goddess associated with fertility, the earth, and prophetic inspiration, often linked to rural life and nature.
-
D.
Fauna
Fauna is a central character in John Steinbeck’s novel "Sweet Thursday," known as the sharp-witted, maternal madam who oversees the Bear Flag brothel in Cannery Row.
-
E.
Ikan
Ikan is an alternative name for the Ukaan language, a lesser-known Niger-Congo language spoken in parts of Nigeria.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5b8ee96988190bf247b986777945c |
completed | April 20, 2026, 5:26 a.m. |
Created at: April 10, 2026, 11:56 a.m.