Triple
T18326796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rondslottet |
E439029
|
entity |
| Predicate | nearestSettlement |
P3883
|
FINISHED |
| Object | Otta |
—
|
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: Otta | Statement: [Rondslottet, nearestSettlement, Otta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Otta Context triple: [Rondslottet, nearestSettlement, Otta]
-
A.
Otta
chosen
Otta is a small Norwegian town known as a regional transport hub and gateway to popular mountain and national park areas.
-
B.
Ott
Ott is a surname most famously associated with Mel Ott, a Hall of Fame Major League Baseball slugger for the New York Giants.
-
C.
Ota
Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
-
D.
Ota
Ota is a civil parish in Portugal, known for its location within the municipality of Alenquer in the Lisbon District.
-
E.
Ota
Ōta is a large ward in southern Tokyo, Japan, known for Haneda Airport, residential neighborhoods, and a mix of industrial and commercial areas.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aab3e7c81909b1c0a688707dfd6 |
completed | April 19, 2026, 5:02 p.m. |
Created at: April 10, 2026, 10:36 a.m.