Triple

T1806112
Position Surface form Disambiguated ID Type / Status
Subject Saint Catherine E40222 entity
Predicate roadAccessFrom P22549 FINISHED
Object Dahab E62531 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: Dahab | Statement: [Saint Catherine, roadAccessFrom, Dahab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dahab
Context triple: [Saint Catherine, roadAccessFrom, Dahab]
  • A. Dahab chosen
    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.
  • 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. Hurghada
    Hurghada is a major Egyptian Red Sea resort city known for its beaches, diving, and tourism industry.
  • D. Ras al-Ghar
    Ras al-Ghar is a key coastal military installation in Saudi Arabia that serves as one of the principal bases for the Royal Saudi Naval Forces.
  • 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_69a88643a3388190a612f2ebe1fb29e7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa659798b88190bd3070349ce6bebb completed March 6, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1baea1c8190a452ffb17dc91aa0 completed March 8, 2026, 7:44 p.m.
Created at: March 4, 2026, 7:32 p.m.