Triple
T13398200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moskenesøya |
E319755
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object | Ramberg |
E1037620
|
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: Ramberg | Statement: [Moskenesøya, hasVillage, Ramberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramberg Context triple: [Moskenesøya, hasVillage, Ramberg]
-
A.
Ramberg
chosen
Ramberg is a small coastal village in Norway’s Lofoten archipelago, known for its white-sand beach and dramatic surrounding mountains.
-
B.
Ruttenberg
Ruttenberg is a surname most notably associated with Joseph Ruttenberg, an acclaimed cinematographer in American cinema.
-
C.
Rattenberg
Rattenberg is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany, known for its rural setting and traditional Bavarian character.
-
D.
Rettig
Rettig is a surname of German origin borne by various notable individuals across fields such as law, politics, and the arts.
-
E.
Rougham
Rougham is a village and civil parish in the English county of Suffolk, known for its rural character and historic church.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d9e7348190844e11dd6cbd13b0 |
completed | April 12, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f73983b8f08190bf4d1a64c0beab97 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:34 p.m.