Triple
T22331927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fering |
E552043
|
entity |
| Predicate | hasAutonym |
P1435
|
FINISHED |
| Object | Fering |
—
|
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: Fering | Statement: [Fering, hasAutonym, Fering]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fering Context triple: [Fering, hasAutonym, Fering]
-
A.
Fering
chosen
Fering is a North Frisian dialect spoken primarily on the island of Föhr in Germany.
-
B.
Farum
Farum is a suburban town in eastern Denmark located in the Furesø Municipality on the island of Zealand.
-
C.
Fregon
Fregon is a remote Aboriginal community in South Australia closely associated with the Pitjantjatjara people and their traditional lands.
-
D.
Feresten
Feresten is the surname of Spike Feresten, an American television writer, comedian, and talk show host known for his work on shows like Seinfeld and Late Show with David Letterman.
-
E.
Faya
Faya is a town in northern Chad that serves as an important oasis and regional administrative center in the Sahara Desert.
- 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_69e11e482f788190b78d1588fc26d606 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1577b555c8190ac61c026ee7dfb2b |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:43 p.m.