Triple
T3595371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Sea Governorate |
E76124
|
entity |
| Predicate | hasResortArea |
P10436
|
FINISHED |
| Object |
El Gouna
El Gouna is a modern, privately developed resort town on Egypt’s Red Sea coast, known for its lagoons, beaches, and upscale tourist facilities.
|
E372368
|
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: El Gouna | Statement: [Red Sea Governorate, hasResortArea, El Gouna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Gouna Context triple: [Red Sea Governorate, hasResortArea, El Gouna]
-
A.
Olona
The Olona is a river in northern Italy that flows through the Lombardy region, including the city of Milan.
-
B.
Plage des Canoubiers
Plage des Canoubiers is a popular sandy beach near Saint-Tropez on the French Riviera, known for its calm waters and relaxed, family-friendly atmosphere.
-
C.
Saint-Tropez
Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
-
D.
Plage des Sabias
Plage des Sabias is a small, picturesque sandy beach on the Île d’Yeu off France’s Atlantic coast, known for its sheltered cove and clear waters.
-
E.
Bertioga
Bertioga is a coastal municipality in the state of São Paulo, Brazil, known for its beaches and Atlantic Forest landscapes.
- 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: El Gouna Triple: [Red Sea Governorate, hasResortArea, El Gouna]
Generated description
El Gouna is a modern, privately developed resort town on Egypt’s Red Sea coast, known for its lagoons, beaches, and upscale tourist facilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: El Gouna Target entity description: El Gouna is a modern, privately developed resort town on Egypt’s Red Sea coast, known for its lagoons, beaches, and upscale tourist facilities.
-
A.
Olona
The Olona is a river in northern Italy that flows through the Lombardy region, including the city of Milan.
-
B.
Plage des Canoubiers
Plage des Canoubiers is a popular sandy beach near Saint-Tropez on the French Riviera, known for its calm waters and relaxed, family-friendly atmosphere.
-
C.
Saint-Tropez
Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
-
D.
Plage des Sabias
Plage des Sabias is a small, picturesque sandy beach on the Île d’Yeu off France’s Atlantic coast, known for its sheltered cove and clear waters.
-
E.
Bertioga
Bertioga is a coastal municipality in the state of São Paulo, Brazil, known for its beaches and Atlantic Forest landscapes.
- 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_69ad85d8042081908af94a04c410dec0 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc15f41cc819085b3e897d823757d |
completed | March 8, 2026, 6:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b403130cf081909bb90800d7dc2d6f |
completed | March 13, 2026, 12:29 p.m. |
| NEDg | Description generation | batch_69b40e244db08190bbe9053619820ae8 |
completed | March 13, 2026, 1:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b42d8084c88190a2aae4a883d050a0 |
completed | March 13, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:22 p.m.