Triple
T18019761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OMR |
E431085
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Madeira |
—
|
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: Madeira | Statement: [OMR, hasMember, Madeira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madeira Context triple: [OMR, hasMember, Madeira]
-
A.
Madeira
chosen
Madeira is a Portuguese archipelago in the North Atlantic Ocean known for its rugged volcanic landscapes, mild subtropical climate, and namesake fortified wine.
-
B.
Azores
The Azores are a remote Portuguese archipelago in the North Atlantic Ocean, known for their volcanic landscapes, lush greenery, and mild maritime climate.
-
C.
Ilha de Faro
Ilha de Faro is a coastal barrier island in southern Portugal known for its sandy beaches, lagoon landscapes, and role as a popular seaside destination near the city of Faro.
-
D.
Madalena, Azores
Madalena is a coastal town and municipality on the island of Pico in Portugal’s Azores archipelago, known for its volcanic landscapes, vineyards, and role as a local transport and tourism hub.
-
E.
Arronches
Arronches is a small Portuguese municipality in the Alentejo region, known for its rural landscape, traditional architecture, and proximity to the Spanish border.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b9c09fdc819097a7fa07d44b0505 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 10:24 a.m.