Triple

T13366636
Position Surface form Disambiguated ID Type / Status
Subject Aswan Museum E318953 entity
Predicate nearbyAttraction P3449 FINISHED
Object Aswan city center E11620 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: Aswan city center | Statement: [Aswan Museum, nearbyAttraction, Aswan city center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aswan city center
Context triple: [Aswan Museum, nearbyAttraction, Aswan city center]
  • A. Aswan chosen
    Aswan is a historic city in southern Egypt on the Nile River, known for its ancient temples, quarries, and the nearby Aswan High Dam.
  • B. Abu Simbel town
    Abu Simbel town is a small settlement in southern Egypt best known as the modern community serving visitors to the famous rock-cut Abu Simbel temples near the Sudanese border.
  • C. Shebin El Qanater
    Shebin El Qanater is a city in Egypt’s Qalyubia Governorate, located in the Nile Delta north of Cairo.
  • D. Beni Suef city
    Beni Suef city is an urban center in Upper Egypt located on the west bank of the Nile, known as an important regional hub for agriculture, industry, and administration.
  • E. Sadat City
    Sadat City is a planned industrial and residential city in Egypt, developed as part of the country’s strategy to create new urban centers and relieve population pressure on major metropolitan areas.
  • 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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadcd652d48190a782fd1f57f34b6a completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f754718a388190b4b85151a4694435 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:32 p.m.