Triple
T22468952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A6 motorway |
E555436
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Spiez |
—
|
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: Spiez | Statement: [A6 motorway, passesNear, Spiez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spiez Context triple: [A6 motorway, passesNear, Spiez]
-
A.
Spiez
chosen
Spiez is a picturesque Swiss town in the Bernese Oberland, known for its lakeside setting, historic castle, and views of the surrounding Alps.
-
B.
Spynie
Spynie is a small settlement in Moray, Scotland, historically associated with the nearby medieval Spynie Palace.
-
C.
Spio
Spio is a figure from Greek mythology, traditionally known as one of the Nereids, the sea nymph daughters of Nereus and Doris.
-
D.
Spotnitz
Spotnitz is a surname most notably associated with Frank Spotnitz, an American television writer and producer known for his work on series such as The X-Files.
-
E.
Spickler
Spickler is the birth surname of American actress and producer Mimi Rogers.
- 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15bdda62c8190937ac13a4481b4b7 |
completed | April 29, 2026, 1:16 a.m. |
Created at: April 16, 2026, 8:48 p.m.