Triple

T3595327
Position Surface form Disambiguated ID Type / Status
Subject Red Sea Governorate E76124 entity
Predicate capital P234 FINISHED
Object Hurghada E72341 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: Hurghada | Statement: [Red Sea Governorate, capital, Hurghada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hurghada
Context triple: [Red Sea Governorate, capital, Hurghada]
  • A. Hurghada chosen
    Hurghada is a major Egyptian Red Sea resort city known for its beaches, diving, and tourism industry.
  • B. Sharm El Sheikh
    Sharm El Sheikh is a popular Egyptian resort city on the southern tip of the Sinai Peninsula, known for its Red Sea beaches, coral reefs, and diving.
  • C. Dahab
    Dahab is a small Egyptian resort town on the southeast coast of the Sinai Peninsula, known for its laid-back atmosphere, diving spots, and windsurfing.
  • D. Zagazig
    Zagazig is a city in Egypt’s Nile Delta that serves as an important regional center for agriculture, education, and transportation.
  • E. Marsa Matruh
    Marsa Matruh is a coastal city in northwestern Egypt on the Mediterranean Sea, known as a popular summer resort and gateway to nearby beaches and historical sites.
  • 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_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.
Created at: March 8, 2026, 3:22 p.m.