Triple

T960480
Position Surface form Disambiguated ID Type / Status
Subject Red Sea E20723 entity
Predicate hasCityOnCoast P969 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, hasCityOnCoast, Hurghada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hurghada
Context triple: [Red Sea, hasCityOnCoast, 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b4144c208190980936347a95e233 completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1cd72fe88190a7cdfe1afc123edd completed March 7, 2026, 12:40 p.m.
Created at: March 1, 2026, 7:40 p.m.