Triple
T23351839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lierne |
E592933
|
entity |
| Predicate | borderWith |
P224
|
FINISHED |
| Object | Grong |
—
|
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: Grong | Statement: [Lierne, borderWith, Grong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grong Context triple: [Lierne, borderWith, Grong]
-
A.
Grong
chosen
Grong is a rural municipality in Trøndelag county, central Norway, known for its forests, rivers, and role as a regional transport and service center in the Namdalen district.
-
B.
Grunnegs
Grunnegs is the local endonym for the Gronings dialect of Low Saxon spoken in the Dutch province of Groningen and surrounding areas.
-
C.
Gruden
Gruden is a surname most prominently associated with Jon Gruden, a former NFL head coach and television analyst.
-
D.
Guran
Guran is a small village in the municipality of Vodnjan in the Istria region of Croatia, known for its rural character and traditional Mediterranean landscape.
-
E.
Gorst
Gorst is a surname most notably associated with Sir Eldon Gorst, a British colonial administrator who served as Consul-General in Egypt in the early 20th century.
- 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_69e25d24d2a4819092e6ede74c2a918d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19a1401748190b77df0a45c2aeebf |
completed | April 29, 2026, 5:41 a.m. |
Created at: April 17, 2026, 5:20 p.m.