Triple
T1136415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mallorca |
E23149
|
entity |
| Predicate | hasBeach |
P1922
|
FINISHED |
| Object |
Magaluf
Magaluf is a popular resort town on the southwest coast of Mallorca, Spain, known for its sandy beaches and vibrant nightlife.
|
E130707
|
NE FINISHED |
How this triple was built (4 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: Magaluf | Statement: [Mallorca, hasBeach, Magaluf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magaluf Context triple: [Mallorca, hasBeach, Magaluf]
-
A.
Saint-Tropez
Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
-
B.
Tarifa
Tarifa is a coastal town in southern Spain known as the southernmost point of mainland Europe and a major destination for wind sports like kitesurfing and windsurfing.
-
C.
Gurzuf
Gurzuf is a coastal resort settlement on the southern Crimean coast, known for its scenic landscapes, beaches, and historic sites.
-
D.
Lara Beach
Lara Beach is a popular, long sandy resort beach on Turkey’s Mediterranean coast, known for its luxury hotels and proximity to the city of Antalya.
-
E.
Olhão
Olhão is a coastal city in Portugal’s Algarve region, known for its fishing port, historic waterfront, and access to the Ria Formosa lagoon and nearby islands.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Magaluf Triple: [Mallorca, hasBeach, Magaluf]
Generated description
Magaluf is a popular resort town on the southwest coast of Mallorca, Spain, known for its sandy beaches and vibrant nightlife.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magaluf Target entity description: Magaluf is a popular resort town on the southwest coast of Mallorca, Spain, known for its sandy beaches and vibrant nightlife.
-
A.
Saint-Tropez
Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
-
B.
Tarifa
Tarifa is a coastal town in southern Spain known as the southernmost point of mainland Europe and a major destination for wind sports like kitesurfing and windsurfing.
-
C.
Gurzuf
Gurzuf is a coastal resort settlement on the southern Crimean coast, known for its scenic landscapes, beaches, and historic sites.
-
D.
Lara Beach
Lara Beach is a popular, long sandy resort beach on Turkey’s Mediterranean coast, known for its luxury hotels and proximity to the city of Antalya.
-
E.
Olhão
Olhão is a coastal city in Portugal’s Algarve region, known for its fishing port, historic waterfront, and access to the Ria Formosa lagoon and nearby islands.
- F. None of above. chosen
Provenance (5 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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc2300c481908c60fbb1188c37c5 |
completed | March 1, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac59ae5f20819093f8acc3ba7a6638 |
completed | March 7, 2026, 5 p.m. |
| NEDg | Description generation | batch_69ac5b5e2c688190a7d4998a3ed0f443 |
completed | March 7, 2026, 5:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac5bb6e78c8190a34ecbc246f72ff6 |
completed | March 7, 2026, 5:09 p.m. |
Created at: March 1, 2026, 7:44 p.m.